Patterns of Liver Gene Expression Governed by TR

Patterns of Liver Gene Expression Governed by TR�

AMILCAR FLORES-MORALES, HJALMAR GULLBERG, LEANDRO FERNANDEZ,NINA STÅHLBERG, NORMAN H. LEE, BJORN VENNSTROM, AND GUNNAR NORSTEDT

Departments of Molecular Medicine (A.F.-M., N.S., G.N.) and Cell and Molecular Biology (H.G., B.V.),Karolinska Institute, Stockholm 17176, Sweden; Health Science Center (L.F.), Pharmacology Section,Las Palmas de Gran Canaria University, 35080 Las Palmas, Spain; and Department of FunctionalGenomics (N.H.L.), Institute for Genomic Research, Rockville, Maryland 20850

Several metabolic processes in the liver are regu-lated by thyroid hormone (T3). Gene expressionprofiles of livers from normal and TR�-deficientmouse strains should allow the classification ofrapid and sustained effects of T3, as well as iden-tification of target genes that are dependent onTR�. The immediate and long-term T3 regulation ofabout 4000 genes in livers from hypo- and hyper-thyroid wild-type and TR�-deficient mice was an-alyzed using cDNA microarrays. T3 was found toregulate more than 200 genes, and among these,more than 100 were previously not described. Sixtypercent of all these genes show dependence onthe TR� gene for T3 regulation, indicating thatTR�1 may have previously unknown functions in

the liver. Analysis of the gene expression patternsshowed a clear functional distinction betweenrapid (2 h) actions of T3 and late effects, seen after5 d of sustained T3 treatment. Many metabolic ac-tions were rapidly executed, whereas effects onmitochondrial function, for example, were seen af-ter the sustained T3 treatment. As compared withwild-type controls, TR��/�mice exhibited ele-vated expression of some target genes and re-duced levels of others, indicating that both directand indirect gene regulation by TRs in liver is com-plex and involves both ligand-dependent and -in-dependent actions by the major TR isoforms.(Molecular Endocrinology 16: 1257–1268, 2002)

THYROID HORMONE (T3) is essential for normaldevelopment, differentiation, and maintenance of

metabolic balance in mammals. T3 exerts its pleiotro-pic actions through binding to specific receptors thatbelong to the nuclear hormone receptor superfamily(1). T3 receptors (TRs) are encoded by two separategenes, TR� and TR�, which are located on differentchromosomes. The TR genes � and � generate severalT3-binding receptors, TR�1 and TR�1–3, that mediatethe effects of T3. A variant receptor protein, TR�2,does not bind T3 and its exact functions are unclear.The different receptor isoforms contain highly homol-ogous DNA binding, ligand binding, and transactiva-tion domains and, as a consequence, they bind similarthyroid hormone response elements in DNA and ex-hibit similar ligand-dependent transactivation activityin vitro (2). TRs can either suppress or induce expres-sion of a target gene and recently, Feng et al. (3)reported that more than half of the target genes in liverare negatively regulated by T3.

The different TR isoforms mediate receptor-specificphysiological activities despite their structural similar-ities (4). Mice with a targeted disruption of the TR�gene show hyperthyroxinemia and an impaired T3-induced repression of the pituitary TSH gene. Thesemice also show impairment of the auditory system and

resistance to hypercholesterolemia under hypothyroidconditions but do not exhibit major impairment ingrowth or additional alterations in neurological func-tions (4–6). On the other hand, TR�1 deficiency yieldsan abnormal heart rate and lower body temperature(5), whereas TR�2 deficient mice, which overexpressTR�1, exhibit a mixture of hypo- and hyperthyroidfeatures (7). Interestingly, mice devoid of both theTR�1 and TR�2 isoforms become progressively hypo-thyreotic, exhibit growth retardation, diminished bodytemperature, and delayed maturation of bone and in-testine, and die within 5 wk after birth (8). The differentpatterns of the expression of the different TRs mayaccount for their phenotypic differences. Neverthe-less, there are few tissues that exclusively express oneform of the receptor. Instead, several forms are coex-pressed at a variable ratio, allowing the possibility foroverlaps in receptor actions (9).

The effects of T3 in the liver involve T4 turnover,regulation of triglycerides, and cholesterol metabo-lism, for example, as well as lipoprotein homeosta-sis (10). The hormone also modulates other cellularprocesses such as cell proliferation (11) and mito-chondrial respiration (12). TR� is the prevalent TR inliver representing 85% of the T3-binding activity(13). TR�-deficient mice express similar amounts ofTR�1 as the wild-type (WT) animals but show resis-tance to some of the T3 actions. TR�-deficient micefail to lower serum cholesterol levels in response toT3 (10) and express low levels of spot14 (13) and5�-deiodinase-1 (14).

Abbreviations: CoA, Coenzyme A; Cy, cyanine; FAS, fattyacid synthase; GAPDH, glyceraldehyde-3-phosphate dehy-drogenase; G6P, glucose-6-phosphate; LID, low-iodine diet;MMI, methimazole; 6PGDH, 6-phosphogluconate dehydro-genase; RPA, ribonuclease protection assay; WT, wild-type.

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To extend the understanding of T3 regulation ofcentral metabolic processes in liver, we determinedthe immediate and the long-term expression of about4,000 genes in liver samples from hypothyroid wild-type (WT) and TR�-deficient mice using DNA micro-array technology. Our results identified a large numberof T3-regulated genes not previously described in theliver and demonstrated the difference between earlyand late effects of T3 in this target tissue. A highdegree of dependence on TR� for the actions of T3

was also observed.

RESULTS

T3 treatment of hypothyroid mice is expected to triggera complex gene-regulatory response in liver, withgenes being up- or down-regulated with variable ki-netics. The predominance of �R� over TR�1 in theliver predicts a major role for �R�. To test these hy-potheses we compared gene expression patterns ofhypothyroid WT and TR��/� mice with those treatedwith T3 for 2 h and 5 d as well as between hypothyroidTR��/� and WT mice. This allowed us to identifyrapidly responsive genes including a subset that isTR� dependent, and genes that respond to sustainedhormonal treatment and which therefore may be indi-rectly regulated. A summary of the experimental de-sign is shown in Fig. 1. In brief, mRNA was isolatedfrom livers of hypothyroid WT and TR��/� mice be-fore and after T3 treatment. Subsequently, globalchanges in gene expression induced by T3 were ana-lyzed using a DNA microarray containing 4000 cDNAsof rat or mouse origin. We have chosen to denotegenes as T3 regulated or TR� dependent if their levelof expression is changed by 70% or more in a statis-tically significant fashion. This level of change haspreviously been shown to be valid when comparedwith other direct methods, such as Northern Blot, ri-bonuclease protection assay (RPA), and RT-PCR (15–17) (see also Table 3). The statistical analyses aredetailed in Materials and Methods.

Of the 4000 cDNA clones analyzed, around 1900showed hybridization, and more than 250 showed re-activity to T3 in at least one of the time points analyzed.When measured after 2 h, T3 down-regulated 72 tran-scripts in WT livers by more than 70% whereas 73were up-regulated to the same extent. In contrast, only84 genes responded to T3 in �R�-deficient mice to thesame extent, suggesting that 50% of the genes rapidlyregulated by T3 in liver require TR�. Certain genesresponded to T3 in livers from TR��/� mice, suggest-ing a partial or complete independence of TR�. Thedistribution of T3-regulated genes within functionalcategories is shown in Fig. 2. The identities of genesshowing variation by a factor of 2 or more in selectedcategories are shown in Table 1 (the complete list canbe found in Table 4, which is published as supplemen-tal data on The Endocrine Society’s Journals Onlineweb site, http://mend.endojournals.org/).

To determine the extent of TR� dependence in theWT animals, we performed a cluster analysis of ex-pression data using the K-means algorithm. Before thealgorithm was applied, data were selected on the ba-sis of fold change as explained above. A database wasassembled with the fold change in gene expression ineach of the experiments. The data for each gene wererepresented as a four-dimensional vector with eachpoint representing ratios from one type of experimen-tal situation. To study the extent of TR� contributionindependently of the magnitude of the changes inexpression levels, the expression data were trans-formed to place all the measurements within the samerange (see also Materials and Methods). K-meansclustering was performed using a dot product calcu-lation to determine the distance between vectors. Fig-ure 3 shows the clusters A, B, C, E, F, K, L, M, and Nof the 15 clusters generated. Clusters A–C indicate T3

up-regulated genes that are highly or partially TR�dependent in immediate (A) or long-term (B and C)hormonal responses. Genes down-regulated by T3 in aTR�-dependent fashion are found in E and F. Note-worthy is the existence of clusters that representgenes that are regulated by T3 in liver independently ofTR� receptor expression (clusters K, L, M, and N).These genes may represent direct targets of TR�1 orproducts of a secondary phenomena resulting fromlong-term adaptation of the tissue to TR� deficiency.Genes in Table 1 are annotated in relation to the clus-ter analysis. The complete cluster analysis can befound in Fig. 5, which is published as supplementaldata on The Endocrine Society’s Journals Online website.

TRs can bind to specific DNA response elementsindependently of ligand occupancy. To test whetherthe genes defined above as TR� dependent were alsoregulated by the unliganded receptor, we determinedthe expression ratios of genes from hypothyroidTR�(�/�) and hypothyroid WT animals. Table 2 showsthat 45 genes were differentially expressed (70% up-or down-regulated): 22 were increased and 23 weredecreased in TR��/� mice as compared with WT.

Fig. 1. Design of Pairwise ComparisonsThe actions of T3 on liver gene expression were evaluated

at two different time points: 2 h and 5 d in both TR��/� andin WT hypothyroid animals. Liver mRNA was isolated fromWT and TR��/� mice that were either hypothyroid or hor-mone treated for either 2 h or 5 d. mRNA was labeled byreverse transcription in the presence of Cy3- or Cy5-dUTPand was used to perform altogether five pairwise compari-sons of gene expression profiles as indicated by the arrows.Solid arrowheads indicate Cy5 labeling and open arrowheadsindicate Cy3 labeling.

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The changes in gene expression detected in hypothy-roid TR� �/� mice resembled those induced by T3 inWT mice since about 80% of those genes were pre-viously characterized as T3 responsive. This groupincludes genes up-regulated by T3 in a TR�-depen-dent fashion (Table 2, marked in bold).

To verify our microarray analysis, we measured RNAlevels either by Northern blots (Fig. 4, upper panel, andTable 3) or RPAs (Fig. 4, lower panel, and Table 3).Probes for nine different genes were used, and theexpression levels were put in relation to control values.A comparison of these data with the microarray resultsfor the corresponding genes gave a correlation coef-ficient of 0.92. This result confirms the validity of themicroarray data.

DISCUSSION

Eleven percent of the hepatic genes (201 of 1900)measured in our array responded to T3 in hypothyroidWT mice, and about 100 of these have no prior recordof being influenced by T3. The fraction of T3-regulatedgenes was somewhat higher than the 8% previouslyreported (18), which may be due to differences inexperimental design such as the aim to define thefunctional differences between rapid (2 h) and sus-tained (5 d) T3 effects. The distinction between theseeffects is of interest because the fast respondinggenes are likely to be direct targets whereas many ofthe late responding ones may be indirectly regulatedas a result of intermediary transcription factors, mRNA

stability changes, or other physiological long-term ef-fects caused by T3 treatment.

Changes in Gene Expression Patterns Inducedby T3

The T3-responsive hepatic genes were categorized toinclude all major liver functions. Differences were ev-ident among categories in relation to their temporalresponsiveness to T3. For example, the effects of T3 onlipogenic genes were in general rapid, and in somecases transient, whereas the effects of T3 on genes forthe mitochondrial respiratory chain, transcription fac-tors, and protein turnover were of a long-term nature(Fig. 2).

A K-means cluster analysis allowed the classifica-tion of T3 effects in relation to the extent of TR� de-pendence (Fig. 3). Both genes with a rapid or a late T3

response showed dependence of TR� (Fig. 3 and Ta-ble 1). However, genes belonging to certain metabolicclass were not limited to specific clusters, with theexception of cluster A, which contains rapidly respon-sive genes for lipogenic enzymes dependent on TR�.Moreover, the dependance on TR� could be eitherdirect or an indirect effect of the hormone. The differ-ences in T3 action between the TR��/� and WT miceare likely to be due to the specific contribution of TR�,as it is the most abundant receptor isoform in liver. Thecontent of TR�1 and TR�2 in TR��/� mice does notdiffer from that found in the WT controls (6, 13, 14) (seealso Table 2), indicating that compensation by in-creased expression of TR�1 does not occur.

Fig. 2. Functional Classification of T3-Regulated Genes in Liver from WT and TR��/� MiceThe experimental design is described in Materials and Methods and in Fig. 1. T3 regulation, defined as more than 70% variation,

was then determined by DNA microarray technology comparing cDNA from T3-treated to cDNA from hypothyroid mice. The lengthof the bars represents the number of T3-regulated genes in each functional category. Within each functional category, differentcolors indicate the number of genes that were regulated 2 h after a single injection of 5 �g T3 and 5 �g T4 (2 h), genes regulatedafter 5 d of one daily 5-�g T3 injection (5d), and those genes regulated after both 2 h and 5 d of hormone injections (2 h and 5 d).

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Table 1. T3-Regulated Genes in Livers of WT and TR� (�/�) Hypothyroid Mice

Clone IDa Gene Name

T3 TreatedSAMb

ClustercWT TR��/�

2 h 5 d 2 h 5 d 2 h 5 d

Glucose and pyruvate utilizationRGIAE68 UDP-Glucose pyrophosphorilase 0.42 0.27 0.44 0.66 * ORGIAJ68 Glucose-6-phosphatase 2.23 0.71 0.65 0.8 * ARGIAJ80 Fructose-1,6-bisphosphatase 0.58 0.35 0.66 0.87 * FRGIAQ41 L-type pyruvate kinase 0.49 0.25 0.3 0.42 * * ORGIBB52 Aldolase B 0.45 0.21 0.43 0.54 * O

Lipogenic enzymesRGIAN54 FAS (EC 2.3.1.85) 3.39 0.9 1.11 0.82 * ARGIAU16 6-Phosphogluconate dehydrogenase 2.43 0.98 1.29 1.11 * ARNAC07 Hepatic product spot 14 6.64 2.32 0.33 0.64 * * ARGIAB17 Carnitine o-acetyltransferase 2.63 0.88 2.91 1.34 KRGIBC21 Acyl-CoA synthetase 5 2.04 0.73 1.75 1.01 * KRGIAE85 Glucose-6-P dehydrogenase 1.93 1.28 2.04 0.91 KRGIAE91 Squalene synthetase 2.57 1.14 1.61 1.35 KRGIAN56 Cytosolic malic enzyme 6.11 2.52 3.42 1.71 * * BRGIAQ69 Farnesyl pyrophosphate synthetase 2.87 1.97 1.24 0.99 * * BRGIAE62 Stearyl-CoA desaturase 2.36 0.16 1.83 0.41 * * JRGIAA92 NADH-cytochrome b5 reductase 1.26 0.41 0.93 0.6 * * J

Lipid mobilization and peroxisomal �-oxidationRGIAJ92 Peroxisomal enoyl-CoA hydratase 7.87 1.73 13.61 2.99 * * KRGIAX68 Cytochrome P450 IVA3 7.22 0.87 18.01 4.41 * * KRGIBC49 Lipoprotein lipase 2.07 1 3.76 1.98 * * LRGIAV01 Fatty acid transporter (FAT) 2.01 0.31 3.33 0.84 * * IRNAA94 Fatty acid binding protein 1.13 0.43 1.81 0.46 * JRNAB78 Apolipoprotein CI 1.04 0.47 1.12 1.17 * IRGIBB12 Peroxisomal phytanoyl-CoA hydroxylase (PHYH) 0.72 0.45 0.7 0.86 * FRGIAF89 Apolipoprotein A-IV 0.35 0.69 0.32 0.42 N

Mitochondrial respirationRGIAN07 F1F0-ATP synthase, g subunit 1.7 2.54 1.07 1.36 * * CRGIAG42 Cytochrome C oxidase, subunit VIIa 1.53 1.87 1.01 1.09 * * CRGIAR15 Ubiquinol-cytochrome c reductase hinge protein (UQCRH) 1.33 1.87 1.07 1.14 * * CRGIAN27 Ubiquinol-cytochrome-c reductase 7.2 kDa protein 1.77 2.22 1.28 1.37 * * DRGIAK10 Cytochrome c 1.66 2.08 1.37 1.41 * * DRGIAG78 NADH-ubiquinone oxidoreductase subunit CI-SGDH 1.5 1.76 1.18 1.25 * * DRGIAQ55 NADH-ubiquinone oxidoreductase subunit 3 1.28 1.8 1.59 1.39 D

Intermediary metabolismRGIAM95 Nudix 7 4.78 7.75 0.64 1.63 * * CRGIAC24 Cyclohydrolase I 2.16 1.74 1.32 1.18 * * BRGIAC56 Aromatic L-amino acid decarboxylase 1.72 1.91 1.6 1.29 * BRGIAT07 S-adenosylmethionine decarboxylase 0.39 0.89 0.59 0.67 * NRGIAM38 Catechol O-methyltransferase 0.77 0.41 0.67 0.68 * * ORGIAO37 5-Aminolevulinate synthase 0.48 0.3 0.57 0.63 * ORGIAE79 Ornithine aminotransferase 0.42 0.22 0.27 0.66 * * ORGIBA46 N-GN-G-dimethylarginine dimethylaminohydrolase 1.05 0.33 1.47 0.77 * * J

Signal transductionRGIAR91 IGF binding protein 2 (Igfbp2) 2.82 2.76 2.5 1.55 * BRGIAM83 Highly similar GTPase-activating protein �-GAP 2.39 4.4 0.83 1.48 * * CRGIAL75 PML protooncogene 1.14 1.95 1.2 1.17 * DRGIAJ01 �-Ig 4.25 4.71 2.79 1.41 * * BRGIAU48 N-ras gene for p21 protein 1.79 1.24 1.15 1 * BRGIAM25 14-3-3 protein, �-isoform 2.17 1.93 1.55 1.33 * * BRGIAC53 rab GDP-dissociation inhibitor, � 2.12 1.43 1.42 1.3 B

Genes with a greater than 2-fold increase or decrease are shown. The expression ratios represent the mean of triplicatedeterminations.a Represents our unique clone identifier. Additional information can be found at www.tigr.org.b Asterisks indicate significant differences (q � 0.01) between WT and TR��/� regarding T3 regulation at different time points.q Values were calculated using a SAM test for unpaired samples.c Represents the classification of genes, by K-means clustering, regarding similarities in expression in the four experiments shown(see also Fig. 3).


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The fact that T3 activated a large number of genesalso in the absence of TR� suggests the involvementof TR�1, although other explanations are also possi-ble. Several possibilities that may explain unique andshared effects mediated by TR� and TR�1 are asfollows. First, TR�1 may, in TR��/� mice, substitutefor the absent receptor. Specificity may also be deter-mined by a differential promoter usage by the differentreceptors. TR�1 and TR�, however, exhibit little dif-ference in binding to response elements or in activa-tion of reporter genes (2) and therefore interaction,through, for example, their respective N-terminal do-mains, with other gene regulatory factors could pro-vide such specificity. Alternatively, the TR isoformsmay differ in expression in the different cell types ofthe liver. Answering these questions will have to awaitfurther investigations using either TR�1�/� mice orthe development of a TR�-specific ligand.

One of our objectives was to find genes that are rapidlyand directly induced by TR�. Accordingly, a rapid generegulation by T3, a significantly reduced T3-dependentgene regulation in TR� �/� animals, and an increasedexpression in hypothyroid TR� �/� compared with WT(because unliganded TR suppresses gene expression),would be the hallmark of such target genes. Based onthese criteria, 13 candidates were identified (Table 2, inbold). Although this is as yet a prediction, it is interestingto note that three of these genes are known to be reg-ulated through well defined TREs (19–21).

Putative Liver Functions of T3-Regulated Genes

Although the interpretations must be both cautiousand preliminary, attempts to translate information of

gene expression patterns into function and phenotypeare of interest and should be discussed. In this study,we have chosen to limit this to the effects of T3 onmetabolism and other selected liver functions.

T3 has insulin-like actions on lipogenesis in liver (22)and antiinsulin effects on liver glucose output. Theexpression patterns reveal regulation of several genesdirectly or indirectly involved in fatty acid synthesis(Table 1). De novo fatty acid synthesis requires thesupply of nicotinamide adenine dinucleotide phos-phate, reduced form (NADPH), and acetyl-coenzyme A(CoA) to be used by the cytosolic enzyme fatty acidsynthase (FAS). Nicotinamide adenine dinucleotidephosphate, reduced form, synthesis would be pro-moted by the observed T3 induction of 6-phosphoglu-conate dehydrogenase (6PGDH) and glucose-6-phos-phate dehydrogenase (G6PDH), enzymes belonging tothe oxidative branch of pentose phosphate pathway(23) and by the induction of malic enzyme (13). T3 alsoreduced the expression of key glycolytic enzymes (e.g.fructose 1, 6 biphosphatase, pyruvate kinase, and al-dolase B), an effect that could result in the accumula-tion of glucose-6-phosphate (G6P) to be used in thepentose phosphate pathway. Increased supply of G6Pcould also be achieved by the T3 regulation of theadrenergic pathway, as indicated by the T3 inductionof two key enzymes (cyclohydrolase I and aromaticL-amino acid decarboxylase) in the catecholaminesynthesis pathway. Furthermore, T3 negatively regu-lated phosphodiesterase and induced phosphatidyl-inositol-4-phosphate 5-kinase �, type II, involved inthe synthesis of the second messenger IP3 (24). Theseeffects, combined with up-regulation of the �-adren-ergic receptor (3), could result in an increased hepatic

Table 1. Continued

Clone IDa Gene Name

T3 TreatedSAMb

ClustercWT TR��/�

2 h 5 d 2 h 5 d 2 h 5 d

Signal transductionRGIAJ95 ERK1 0.73 0.46 1.02 0.82 * * FRGIAR61 Adenylate kinase 3 0.6 0.32 0.73 0.61 * GRNAB35 PDE I 0.44 0.36 0.63 1 * * ERGIAV72 Epidermal growth factor 0.78 0.38 0.89 0.9 * * FRGIAD66 Protein phosphatase 2A catalytic subunit, � 0.51 0.26 0.59 0.75 * FRGIAG35 Acyl-CoA-binding protein/diazepam binding inhibitor 2.08 0.81 1.77 1.32 * KRGIBA80 Phosphatidylinositol-4-phosphate 5-kinase �, type II 2.63 4 5.64 3.38 * LRGIBC55 GH receptor 0.53 0.37 0.39 0.57 * * O

TranscriptionRGIAK24 STAT5b 2.16 0.7 1.25 0.71 * ARGIAQ63 DNA-binding protein inhibitor ID-1 2.15 1.78 1.65 1.68 * BRGIAP03 cAMP-dependent transcription factor mATF4 0.97 1.9 0.96 1.08 * DRGIBA55 hPer (circadian pacemaker protein) 0.44 0.53 0.71 0.74 * * ERGIAG73 Transcription elongation factor TFIIS.h 0.42 0.2 0.48 0.79 * FRGIBA40 Interferon regulatory factor 2 0.68 0.37 0.62 0.63 * ORGIBB50 Peroxisome proliferator activated receptor alpha 1.01 0.47 1.11 0.83 * J

Cell proliferation and apoptosisRGIAL89 NGF-inducible protein PC3 0.25 0.28 1.48 1.1 * * ERGIAI87 Cyclin A 2.3 2.47 4.37 2.36 * LRGIAR37 Cyclin I 0.94 0.46 0.98 0.71 * J


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responsiveness to adrenergic receptor stimulation.We have also reproduced the previously describedinduction of glucose-6-phosphatase by T3 (3).

The regulation by T3 of key players in the lipogen-ic and glucogenic pathways, e.g. spot 14, FAS,6PGDH, glucose-6-phosphate dehydrogenase,G6P, and stearyl-CoA desaturase, was rapid andtransient. Such regulation of lipogenic genes mayhelp to explain the apparent contradiction betweenthe lipogenic actions of T3 in liver and the reducedlevels of lipoproteins/lipids achieved by long-termhormonal treatment (10). Furthermore, the T3 regu-lation of FAS, G6P, 6PGDH, phosphofructokinase,and other key enzymes within the lipogenic pathwaywere dependent of the TR� form of the receptor for

their regulation (Table 1 and Fig. 3). The hypothyroidTR��/� mice show an increased expression of asimilar set of lipogenic genes (Table 2) and have, ascompared with controls, reduced levels of lipopro-teins in serum after induction of hypothyroidism (10).Therefore, no linear relationship between the TR�-dependent expression of liver lipogenic enzymesand T3 regulation of serum cholesterol levels isapparent. Nevertheless, it is possible that a lipo-genic stimulus regulates lipoprotein synthesis orassembly (25).

Our results show that apolipoproteins C1 and A-IVwere down-regulated by T3. Because overexpressionof C1 leads to combined hyperlipidemia, reduction ofits expression may mediate some of the beneficial

Fig. 3. TR� Dependence of T3-Regulated Genes in LiverA K-means cluster analysis was performed with expression data normalized so that 1 U represents maximal possible

induction/repression. The expression data used were the mean of three independent hybridizations from a similar number oflabeled cDNA samples. Left panel, The cluster output is shown with the fold change indicated colorimetrically; green colorindicates down-regulation by T3 and red color indicates up-regulation. Individual genes are represented along the vertical axis,whereas experimental conditions are represented horizontally. Right panel, Nine clusters (A, B, C, E, F, K, L, M, and N) are shown.The mean normalized expression values were calculated for each cluster. Significant differences between T3 effects in WT andTR� �/� are indicated. [(*) P � 0.00001].


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effects of the hormone on serum lipoprotein patterns(26). The fact that ApoC1 is suppressed by TR� maycontribute to the resistance of TR� �/� mice to re-duce their cholesterol levels after T3 treatment. The

gene expression pattern also suggests that T3 couldsuppress production of hepatic triglycerides by reduc-ing glycerol 3-phosphate, used in esterification of fattyacids. This effect could derive from the T3 actions on

Table 2. Ligand-Independent Effects of TR�

Clone IDa Name

Hypothyroid T3 Treated

TR��/� vs. WT SDWT TR��/�

2 h 5 d 2 h 5 d

RIAA32 �-2u-Globulin 8.56 0.62 3.46 27.64 0.52 1.89RNAC07 Spot 14 3.4 0.11 6.64 2.32 0.33 0.64RGIAN56 Malic enzyme 2.29 0.07 6.11 2.52 3.42 1.71RGIAT71 Squalene monooxygenase 3.17 0.52 5.48 6.31 2.1 1.72RGIAM95 Nudix7 3.54 0.06 4.78 7.75 0.64 1.63RGIAS25 Podocalyxin 2 0.21 3.93 3.27 2.41 1.57RGIAN54 FAS 2.13 0.16 3.39 0.9 1.11 0.82RGIAJ70 Aquaporin 8 2.34 0.02 3.17 0.24 1.43 0.95RGIAQ69 Farnesyl pyrophosphate synthetase 2.19 0.16 2.87 1.97 1.24 0.99RGIAX93 est 4.81 0.33 2.71 1.16 0.84RGIAU16 6-Phosphogluconate dehydrogenase 1.83 0.19 2.43 0.98 1.29 1.11RGIAM83 Similar to GTP ase activating protein

rhoGAP2.2 0.07 2.39 4.4 0.83 1.48

RGIAJ68 Glucose-6-phosphatase 3.14 0.07 2.23 0.71 0.65 0.8RGIAM82 Similar to hypothetical protein KIAA0670 2.07 0.54 1.83 2.68 0.93 1.49RGIAU48 N-ras p21 protein 1.68 0.04 1.79 1.24 1.15 1RGIAG78 NADH-ubiquinone oxidoreductase subunit

CI-SGDH2.33 0.25 1.5 1.76 1.18 1.25

RGIAI02 Biphenyl hydrolase-related protein 2.47 0.17 1.48 2.25 1.03 1.25RGIAU76 Inhibitor of DNA binding 3 (ID-3) 1.8 0.13 1.43 1.77 0.95 1.09RGIAE62 Stearyl-CoA desaturase 1.8 0.12 2.36 0.16 1.83 0.41RGIBA95 Organic anion transporter OAT-K1 1.77 0.05 0.78 0.79 0.35 0.7RGIAF89 Apolipoprotein A-IV 2.12 0.42 0.35 0.69 0.32 0.42RGIAI11 M. musculus P311 1.81 0.1 0.28 0.69 0.15 0.41RGIAD18 TR� 0.98 0.2 0.97 1.02 1.04 1.05

RGIBB48 Rn.16261/est 0.3 0.03 0.77 0.21 0.8 0.67RGIAL89 NGF-inducible protein PC3 0.3 0.03 0.25 0.28 1.48 1.1RGIAG48 NADP transhydrogenase 0.34 0.02 0.88 0.54 2.14 1.37RGIAM65 est 0.36 0.09 0.9 0.54 0.88 0.76RGIAX68 Cytochrome P450 IVA3 0.37 0.02 7.22 0.87 18.01 4.41RGIAR41 STAT3 interacting protein 1 0.37 0.04 0.86 0.52 1.02 0.82MKAE60 AC005743 0.4 0.01 0.46 0.24 1.44 0.99RNAB57 Haptoglobin mRNA 0.4 0.03 0.73 0.98 1.47 1.78RIAA38 �-1-Macroglobulin 0.42 0.1 0.62 0.35 0.84 0.73RNAA76 Polyubiquitin 0.43 0.09 0.6 0.35 0.8 0.68RGIAV01 Fatty acid transporter 0.46 0 2.01 0.4 3.24 0.85RGIAJ58 est 0.49 0.1 0.87 0.87 1.52 1.14RGIBB45 Nicotinamide N-methyltransferase 0.49 0 0.21 0.57 0.2 0.77RGIAR27 Acyl-CoA:cholesterol acyltransferase, SOAT 0.51 0.11 0.58 0.51 0.98 0.73RNAD39 Phosphoenolpyruvate carboxykinase 0.51 0.02 0.6 1.31 1.02RGIAG17 est 0.51 0.02 1.69 0.33 2.66 0.77RGIAP49 Annexin II/calpactin I heavy chain 0.54 0.06 0.85 0.61 1.89 1.19RGIAN52 TIS11 0.56 0.04 0.73 0.66 1.66 1.29RGIAJ13 Hemoglobin �-chain 0.57 0.03 2.74 3.24 8.23 4.44RGIAF70 Pulmonary flavin-containing

monooxygenase0.58 0.12 1.18 0.4 1.07 1.08

RNAA15 GDP-dissociation inhibitor 0.58 0.02 0.54 0.52 0.87 0.87RGIAW06 est 0.58 0.03 0.31 0.03 0.11 0.51MKAE35 Complement component C3 0.59 0.02 0.5 0.53 0.86 0.98

Ratio of gene expression comparing hypothyroid TR��/� mice to hypothyroid WT mice. The values represent the mean and SD

of triplicate determinations. The effects of T3 treatment on expression of these genes in WT and TR��/� mice are also shownfor comparison.a Clone ID represents our unique clone identifier. Additional information can be found at www.tigr.org.


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the glycolytic pathway (see above) and its known ac-tivation of the mitochondrial glycerol phosphate shut-tle (27).

Our demonstration that T3 treatment inhibits the twokey members of the desaturase complex, steraryl-CoAdesaturase and reduced nicotinamide adenine dinu-cleotide (NADH) cytochrome b5 reductase, indicatesthat the lipid composition of lipoproteins and thereforealso lipoprotein function may be altered. This is fully inconcordance with the known ability of T3 to reduce theratio of unsaturated to saturated fatty acids in very lowdensity lipoprotein (28) particles.

T3 reduces serum cholesterol and a previous studyshowed that 7-� hydroxylase (CYP7A), a major regu-lator of cholesterol degradation and bile acid synthe-sis, is increased by T3 in a TR�-dependent manner(10). Here we show that the enzymes squalene syn-

thetase, farnesyl pyrophosphate synthetase, andsqualene monooxygenase are induced by T3, in afashion similar to hydroxymethylglutaryl-CoA reduc-tase. These enzymes belong to the biosynthetic cho-lesterol pathway and support the concept that T3 canincrease both synthesis and degradation ofcholesterol.

Previous experiments on TR� �/� mice showedthat T3 regulation of energy expenditure in hypothyroidanimals is independent of TR� (13). However, the lateT3 effects seen by us included genes encoding pro-teins involved in the respiratory chain, such as sub-units of reduced nicotinamide adenine dinucleotide-ubiquinone Q reductase, cytochrome c, and the F1F0

ATP synthetase. Some of these genes showed a re-duced expression in TR��/� mice, indicating thatTR� may contribute to the regulation of mitochondrialoxidative phosphorylation in liver. De novo lipid syn-thesis, membrane phospholipid assembly, mitochon-drial DNA replication, and transcription of both nuclearand mitochondrial genes have been linked to theknown stimulation of mitochondriogenesis by T3 (29–32). Our results indicate that the late effects on nuclearencoded genes for mitochondrial proteins may be anindirect action of T3. This is further supported by arecent report (33) on mitochondrial transcription beingmediated by an indirect T3 induction of NRF-1 andPGC-1, known regulators of mitochondrial biogenesis(34).

T3 Effects Related to Proliferation and Signaling

No obvious expression pattern of genes involved in cellproliferation was seen, although several novel effects ofthe hormone were observed. Noteworthy is that severalgenes involved in proliferation were either induced (e.g.N-ras) or repressed by T3 (epidermal growth factor,ERK-1, and MAPK phosphatase). Other genes, associ-ated with tissue differentiation or antiproliferative mecha-nisms, likewise showed an increased (PML: promoter ofacute promyelocytic leukemia) or reduced expression(PC3/BTG2, a p53-regulated protein with antiprolifera-tive actions) (35). Obviously, both proliferation and differ-entiation programs are tightly balanced to ensure theintegrity of liver tissue after T3 treatment. Other signalingmolecules were also either induced or repressed by T3,in a TR�-dependent fashion. The regulation of varioussmall GTPases and some of their regulatory proteinsinvolved in cellular trafficking, cellular motility, and cy-toskeleton rearrangement (36) represents novel actionsof T3.

Some of the T3-regulated genes are also controlledby GH (15, 16). Although it is known that T3 bothregulates GH release and can influence GH effects atits site of action, it is noteworthy that expression ofSTAT5b, a transcription factor that mediates many GHeffects in the liver (37), was rapidly induced by T3 in aTR�-dependent manner. This observation is in full ac-cordance with the well known dependence on T3 ofcertain GH actions in liver (12).

Fig. 4. Confirmatory Analysis of Gene Expression DataEffect of T3 deprivation (HT) and hormone treatment for

either 2 h (2h) or 5 days (5d), of TR��/� and correspondingWT mice, on the abundance of mRNA for spot14, malicenzyme, Nudix7, glucose-6-phosphatase, squalene syn-thase, CD36/fatty acid transporter, GAPDH, FAS, and farne-syl pyrophosphate synthase (FPS). The upper panel is arepresentative mRNA expression analysis by Northern bloton RNA pools. Each pool was obtained by combining RNAprepared from four to six livers as described in Materials andMethods. GAPDH was added as a control for equal loading ofRNA. The lower panel represents expression values obtainedby RPA/solution hybridization assays. The values are ex-pressed in arbitrary units (A.U) calculated as the measuredradioactivity for the specific gene in relation to the measure-ment of GAPDH. The values are the average of four to sixratio determinations corresponding to an equal number ofliver samples in each treatment.


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In summary, the use of DNA microarray technologyon mice with a targeted mutation in the TR� geneallowed us to substantially increase our knowledge onT3 actions in liver. Clearly, T3 regulates the expressionof functionally different sets of genes in temporallydistinct ways. Importantly, the use of TR��/� animalsallowed us to dissect this complex pattern and definea number of T3-responsive genes that are dependenton TR� in vivo. One can envision similar experimentalstrategies to define the contribution of specific tran-scription factors to the in vivo actions of multiple hor-mones and trophic factors.

MATERIALS AND METHODS

Animals and Experimental Design

Male mice aged 2–3.5 months were used. The studies wereapproved by the Institutional Animal Care and Use Commit-tee. TR�-deficient mice were genotyped by Southern blot orPCR analysis using PCR primers specific for the mutant TR�allele, as described previously (6). The genetic background ofthe TR�(�/�) mice is a hybrid of 129/Sv � C57Bl/6J. Themice, their housing conditions, and the procedures for induc-ing hypo- and hyperthyroidism were recently described ingreat detail (38). The mice were divided into groups, eachconsisting of four to six WT and four to six TR��/� animals.At the onset of the experiment, all groups of animals wereprovided a low-iodine diet (LID) (R584, AnalyCen Nordic AB,Lidkoping, Sweden) for 14 d to accustom them to the syn-thetic chow. The mice were then made hypothyroid by inclu-sion of 0.05% methimazole (MMI) and 1% potassium per-chlorate in the drinking water (LID�MMI) for 21 d when on theLID diet. This treatment lowered serum-free T3 to about 2pmol/liter. From d 35, one group of animals were injecteddaily with 5 �g T3 for an additional 5-d period to inducehyperthyroidism (24 h after the last T3 injection serum-free T3was, on average, about 15 pmol/liter). Another group of an-imals was injected with 5 �g T3 and 5 �g T4; on d 35, theanimals in this group were killed 2 h after the T3/T4 injection.

At the time of kill, trunk blood was collected after decapitationand T3 analyses were performed later. We used a subset ofthe animal samples described previously (10), and, conse-quently, the corresponding serum levels of T3 and T4 in theanimals subjected to the different treatments were similar.

Generation of cDNA Microarrays

Approximately 4000 cDNA clones were selected from theTIGR Rat Gene Index (www.tigr.org) and our own collectionof rat and mouse cDNA libraries enriched with hepatic genesof known function (15). Procedures for array fabrication, in-cluding quality controls and sequence verification, have beendescribed elsewhere (15, 16).

RNA Preparation, cDNA Labeling, Purification,and Hybridization

Livers were collected after decapitation and immediately fro-zen on solid CO2. Total RNA was isolated from individuallivers using TRIzol Reagent (Life Technologies, Inc., Gaith-ersburg, MD), according to the protocol supplied by themanufacturer. The quality of the RNA samples was examinedon a denaturing agarose gel. Equal amounts of total RNAfrom five animals in the same experimental group werepooled before mRNA purification. mRNA was purified from 1mg of total RNA using 35 mg oligo(dT)-cellulose (AmershamPharmacia Biotech, Uppsala, Sweden) as previously de-scribed (16).

The protocol employed for probe labeling and purificationwas essentially as described previously (15). Two micro-grams of mRNA were used from each group of animals foreach experiment. Labeled cDNA was produced by oligo-dT-primed reverse transcription reaction using SuperScript II(Life Technologies, Inc.). Oligo dT primers and cyanine (Cy)-labeled nucleotides were obtained from Amersham Pharma-cia Biotech. In the first set of experiments, each hybridizationcompared Cy3-labeled cDNA reverse transcribed frommRNA isolated from livers of young male hypothyroid mice(WT) with Cy5-labeled cDNA isolated from livers of similaranimals treated with T3 for 2 h or 5 d. In another set ofexperiments, Cy3-labeled cDNA reverse transcribed frommRNA isolated from livers of young male hypothyroid micewith a target mutation of TR� gene were compared with

Table 3. Comparison of Gene Expression of Individual Genes in Either TR��/� Mice or WT Controls Determined byNorthern Blota or RNAse Protection Analysisb (A) vs. Microarraysc (B)

Gene Hypothyroid TR��/� vs.Hypothyroid WT (A vs. B)

T3 Induction (A vs. B)

WT TR��/�

2 h 5 d 2 h 5 d

Spot14 3.3**/3.4 10.0**/6.6 2.2/2.3 0.3**/0.3 0.5**/0.6Malic enzyme 2.0**/2.3 8.0**/6.1 2.6*/2.5 4.0**/3.4 2.2**/1.7Nudix7 2.7**/3.5 7.1**/4.8 6.3*/7.8 1.4*/0.6 1.5*/1.6Glucose 6 phosphatase 3.1**/3.1 4.0**/2.2 1.8/0.7 1.4/0.7 0.9/0.8CD36/fatty acid transporter 0.4/0.4 2.8/2.0 0.2/0.4 2.4/3.4 1.3/0.9Squalene synthase 3.2/2.6 1.8/1.1 2.9/1.6 1.6/1.4FAS 2.2*/2.1 2.6**/3.4 1.3/0.9 0.9/1.1 1.1/0.8Farnesyl pyrophosphate synthase 2.1**/2.2 2.5**/2.9 2.0*/2.0 0.8/1.2 1.1/1.0

Expression values were normalized against GAPDH expression and used to either compare differences in gene expression levelbetween hypothyroid TR��/� and WT mice (column 2) or fold induction by T3 injections (columns 3–6).a Northern blot determinations were done both on liver RNA from four to five individual animals and on pooled RNA from four tofive livers with similar results.b RPA (italics) was performed on liver RNA from four to six individual animals in each treatment.c The microarray data are from Tables 1 and 2.* and ** denote significant statistical difference between hypothyroid and T3-treated mice as well as between hypothyroid TR��/�and WT according to t test. **, P � 0.01 and *, P � 0.05.


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Cy5-labeled cDNA isolated from livers of similar animalstreated with T3 for 2 h or 5 d. Finally the gene expression inlivers of TR�(�/�) hypothyroid animals (Cy5 labeled) wascompared with the gene expression of WT animals.

The labeled and purified cDNA was added to the array ata final volume of 15 �l in hybridization buffer (0.75 M NaCl, 75mM Na citrate, 0.2% SDS, 10 �g poly(A) RNA, 10 �g yeasttRNA). The array was covered by a plastic 22 � 22-mm coverslip (Grace Biolabs, Bend, OR) and put in a sealed hybridiza-tion chamber (Corning, Inc., Corning, NY). After the hybrid-ization, which took place at 65 C for 15–18 h, the array waswashed and dried.

Image Analysis, Data Acquisition, andStatistical Evaluation

The array was scanned using a GMS 418 scanner (Affymetrix,Santa Clara, CA). Image analysis was performed using theGenePix Pro software (Axon Instruments, Foster City, CA).Automatic flagging was used to localize absent or very weakspots (�2 times above background), which were excludedfrom analysis. Normalization between the two fluorescentimages was performed, as described previously (15). Theaverage coefficient of variation of ratio measurements (cal-culated as SD/mean) for replicate experiments was 10%(0.1 � 0.09) in the data set generated during this study. Thevariability of the triplicate analysis was estimated using SAMsoftware (39). SAM is a statistical technique for finding sig-nificantly regulated genes in a set of microarray experiments.For each gene i in the array, SAM computes the T-statistic di,a score derived from the changes of genes expression inrelation to the SD of repeated measurements for that gene. Athreshold can be set based on di to identify potentially sig-nificant changes in gene expression. The threshold can beadjusted based on an associated false discovery rate (FDR)value: the percentage of genes expected to be wrongly iden-tified as differentially expressed when a certain threshold (dvalue) is set. To each of the genes in the array a q value isassigned. This value is similar to the familiar P value andmeasures the lowest FDR at which the gene is called signif-icant. According to the SAM analysis, the list of T3-regulatedgenes (Table 1 and Table 4, which is published as supple-mental data) has an associated FDR of less than 1%, mean-ing that of the 250 genes identified less than 3 are expectedto be falsely classified as regulated. To the statistically basedcriteria we have added a further requirement based on theabsolute changes in expression ratios. Only genes with av-erage changes of 70% were counted as differentially ex-pressed. This level of expression changes has been shownby us (15, 16 and Table 3) and others (17) to be reproduciblewhen other direct methods, such as Northern Blot, RPA, andRT-PCR, are used to estimate gene expression. Althoughlower levels of changes in gene expression may have impor-tant biological consequences, insufficient information existsregarding its reproducibility by independent methodologies.

As most of the array elements are rat cDNA clones and theRNAs analyzed were of mouse origin, we performed an ho-mology search where rat cDNA sequences were comparedwith the mouse EST division of the GenBank database usingthe BLAST program (40). The identity of the mouse clone withthe highest sequence homology to the corresponding ratclone is shown in the supplemental data, together with thee-value and the percentage of identity. For each of the mousegenes reported here as being regulated based on a rat probe(array element), a highly homologous mouse clone could beidentified (e-value � e-20). Hence, the high level of homologybetween rat and mouse genes used in this study justifies theuse of rat cDNA clones to measure expression in tissues ofmouse origin. According to the BLAST results, the possibilityof misidentifying a mouse gene as being differentially regu-lated based on an orthologous rat probe is very small andcomparable to the likelihood of cross-hybridization betweentwo distinct genes within the same species (rat). Moreover,

significant cross-hybridization with homologies above 75%has been previously reported using a similar technology (44),which further support the use rat probes to measure ortholo-gous mouse genes.

Confirmatory Gene Expression Analysis

The expression of several of the genes identified as differen-tially expressed by the cDNA microarray analysis was mea-sured using Northern blots or RPA analysis. The expressionof spot14, glucose-6-phosphatase, Nudix7, Malic enzyme,and glyceraldehyde-3-phosphate dehydrogenase (GAPDH)was done both on liver RNA pools from four to six mice andon individual samples with similar results (Fig. 4, upper panel).The measurement of squalene synthase and CD36/fatty acidtransporter was performed only in RNA pools. The expressionof FAS and farnesyl pyrophosphate synthase was measuredby RPA/solution hybridization assays in individual liver sam-ples (Fig. 4B). Probe labeling, hybridization and quantitationwere performed essentially as described previously (10, 16).Expression values were normalized against GAPDH contentand used to calculate the expression ratios corresponding tothe measurements obtained by the cDNA microarrayanalysis.

K-Means Clustering and Statistical Analysis

Clustering analysis was performed essentially as describedelsewhere (41). The fold ratio of gene expression for each ofthe experiments analyzed was scored and filtered as ex-plained above and represents the average of three determi-nations. D-dimensional vectors (d � number of experimentsincluded) were created for each of the N genes included fromthe data set selected as being regulated. The N, D-dimen-sional vectors were normalized to the unit sphere using theCluster program (42) and used as input into K-means clus-tering algorithms. Gene clusters were generated using J-express (43). Mean expression patterns were calculated fromthe normalized gene vectors in the clusters, and the statisticalsignificance was determined using an unequal variance t test.All the computer programs used are freely available atwww.microarrays.org.

Acknowledgments

We thank Dr. Douglas Forrest for providing the TR��/�mice and for his helpful comments on the manuscript.

Received December 10, 2001. Accepted February 20,2002.

Address all correspondence and requests for reprints to:Amilcar Flores-Morales, Center of Molecular Medicine(CMM), L8:01, Karolinska Hospital, 17176 Stockholm, Swe-den. E-mail: [email protected].

A.F.-M. is supported by the University of Applied Sciences(UDCA), Colombia. A.F.-M. and G.N. are supported by theSwedish Medical Research Council; H.G. and B.V. are sup-ported by The Swedish Cancer Society; L.F. is supported bythe Consejerıa de Educacion del Gobierno Autonomo deCanarias, Ministerio de Educacion y Cultura (PM98-0033),Ministerio de Sanidad y Consumo (FIS 1/1000), and ColegioOficial de Medicos de Las Palmas; and N.H.L. is supportedby a National Heart, Lung and Blood Institute Grant,HL-59781.

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Patterns of Liver Gene Expression Governed by TR

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