Genome-wide analysis of Pax8 binding provides new insights into thyroid functions
© Ruiz-Llorente et al.; licensee BioMed Central Ltd. 2012
Received: 3 January 2012
Accepted: 24 April 2012
Published: 24 April 2012
The transcription factor Pax8 is essential for the differentiation of thyroid cells. However, there are few data on genes transcriptionally regulated by Pax8 other than thyroid-related genes. To better understand the role of Pax8 in the biology of thyroid cells, we obtained transcriptional profiles of Pax8-silenced PCCl3 thyroid cells using whole genome expression arrays and integrated these signals with global cis-regulatory sequencing studies performed by ChIP-Seq analysis
Exhaustive analysis of Pax8 immunoprecipitated peaks demonstrated preferential binding to intragenic regions and CpG-enriched islands, which suggests a role of Pax8 in transcriptional regulation of orphan CpG regions. In addition, ChIP-Seq allowed us to identify Pax8 partners, including proteins involved in tertiary DNA structure (CTCF) and chromatin remodeling (Sp1), and these direct transcriptional interactions were confirmed in vivo. Moreover, both factors modulate Pax8-dependent transcriptional activation of the sodium iodide symporter (Nis) gene promoter. We ultimately combined putative and novel Pax8 binding sites with actual target gene expression regulation to define Pax8-dependent genes. Functional classification suggests that Pax8-regulated genes may be directly involved in important processes of thyroid cell function such as cell proliferation and differentiation, apoptosis, cell polarity, motion and adhesion, and a plethora of DNA/protein-related processes.
Our study provides novel insights into the role of Pax8 in thyroid biology, exerted through transcriptional regulation of important genes involved in critical thyrocyte processes. In addition, we found new transcriptional partners of Pax8, which functionally cooperate with Pax8 in the regulation of thyroid gene transcription. Besides, our data demonstrate preferential location of Pax8 in non-promoter CpG regions. These data point to an orphan CpG island-mediated mechanism that represents a novel role of Pax8 in the transcriptional output of the thyrocyte.
KeywordsPax8 ChIP-Seq Expression arrays CpG island CTCF SP1
Gene regulation has been the subject of intense investigation over the past decades, mainly focusing on detailed characterization of a particular gene or gene family. However, genome-wide mapping of protein-DNA interactions and epigenetic marks is essential for a full understanding of transcriptional regulation. A precise map of binding sites for transcription factors (TFs), core transcriptional machinery, and other DNA-binding proteins is necessary to decode the gene regulatory networks and their contribution to developmental processes and human disease . In fact, regulation of gene expression by TFs is one of the major mechanisms for controlling cell proliferation, differentiation, and function.
To elucidate the mechanism(s) operating in the establishment and maintenance of cell-specific differentiation, we used thyroid epithelial cells as a model system. These cells are the largest cell population of the thyroid gland and express different TFs called Nkx2.1, Foxe1, Hhex and Pax8, which define the thyroid differentiated phenotype [2, 3]. It is well known that these factors bind to the promoter regions of thyroid-specific genes, such as the genes encoding Thyroglobulin (Tg), Thyroperoxidase (Tpo), and the Sodium Iodide Symporter (Nis), thus regulating their expression. Nevertheless, despite the key relevance of these TFs for thyroid biology, few studies have described additional loci that are transcriptionally regulated by the above mentioned TFs, nor have sequences been described to which these factors bind in enhancers, silencers, or boundary elements that could potentially regulate the transcription of genes over large distances.
Among these thyroid TFs, Pax8 is a member of the paired box-containing proteins and is expressed in the thyroid and kidney, and in the central nervous system during development . It plays an essential role in the differentiation of thyroid cells and, according to the phenotype of Pax8 knockout mice, it seems to be responsible for the formation of the follicles of polarized epithelial thyroid cells . Also, the association between mutations of PAX8 and congenital hypothyroidism in humans underlines an important function of this transcription factor in thyroid pathologies . In order to better understand its role in the maintenance of thyroid function, we explored the transcriptional profile of Pax8-silenced thyroid cells, and integrated these signals with global cis-regulatory sequencing studies (chromatin immunoprecipitation followed by sequencing; ChIP-Seq).
The ChIP-Seq strategy allowed us to identify a large number of novel in vivo Pax8 binding sites that were significantly associated with CpG islands or high GC content sequences. Interestingly, immunoprecipitated peaks were mainly located along intronic regions and grouped in distal positions with respect to transcriptional start sites. Consensus sequence screening of these areas suggested Pax8 interaction with several core transcriptional elements (motif ten element, Inr, and BRE), transcription factors belonging to the AP1 family, and trans-elements factors involved in high order chromatin structure (CTCF) and remodeling (Sp1). Co-immunoprecipitation and reporter assays demonstrated both physical binding and transcriptional cooperation between CTCF/Sp1 and Pax8. Combining sequencing and expression array data, we ultimately provided insights into Pax8- transcriptional networks in the differentiated thyroid that predict its involvement in relevant biological processes and pathways.
Genomic features associated with Pax8 binding sites
In order to identify the genome-wide binding patterns of Pax8 in differentiated thyroid cells, we performed ChIP-Seq in PCCl3 rat thyrocytes using IP and non-IP conditions. Prior to massive sequencing, both conditions were interrogated to verify Pax8 binding site enrichment by means of semi-quantitative PCR (Additional file 1). Using this approach, we confirmed DNA immunoprecipitation of Pax8 binding regions in the rat Nis and Tpo promoters (Additional file 1A), as previously described [7–9]. Therefore, we considered both IP and non-IP conditions as useful samples to further identify whole genome Pax8 binding sites by means of high throughput sequencing technology. After sequencing analysis, we obtained 11,613,355 and 12,125,758 raw reads for control and IP conditions, respectively. Of these, 6,714,002 (57.8%) and 6,431,519 (53.0%) fulfilled the ≤2 mismatches quality filter.
To further localize regions of Pax8 enrichment, we identified Pax8 peaks genome-wide. Peak detection analysis using MACS defined 13,151 Pax8-enriched regions with an average length of 681 bp (Additional file 2). Visual inspection of the Pax8 binding sites and the profiling data in a genome browser for well-known Pax8 targets like Nis, Tpo, [7, 9] and WT1 (Wilms' tumour gene 1) , showed Pax8 binding sites close to the 5'-UTRs of these genes as previously described. A detailed analysis of Nis (Slc5a5, Na+/I− symporter), whose transcription status is tightly regulated by Pax8 , showed a significant Pax8 binding site overlapping with the Nis upstream enhancer (Additional file 1B). These findings clearly validated ChIP-Seq as an efficient and powerful technique for mapping Pax8 binding sites in PCCl3 cells.
Pax8 immunoprecipitated regions delineate Pax8 consensus core sequence in vivo
Immunoprecipitation data reveals interaction of Pax8 with various TFs
Main DNA binding motifs overrepresented in Pax8-dependent peaks
Matches in Input (n)
Transcription factor II B (TFIIB) recognition element
Human motif ten element
X gene core promoter element 1
Drosophila motif ten element
Initiator (INR) and downstream promoter element (DPE) with strictly maintained spacing
Nuclear respiratory factor 1
GC-Box factors SP1/GC; Stimulating protein 1, ubiquitous zinc finger transcription factor
GC-Box factors SP1/GC; Stimulating protein 1, ubiquitous zinc finger transcription factor
Zinc finger / POZ domain transcription factor
Expression arrays analysis identifies a wide set of loci regulated by Pax8
We used whole genome expression arrays to identify Pax8-regulated genes by comparing expression profiles of Pax8-silenced PCCl3 cells with both scrambled siRNA-treated and wild type (wt) PCCl3 cells. This last condition was included to consistently integrate both expression array signals and global cis-regulatory sequencing studies into the same experimental conditions. Misinterpretation of expression data due to compensatory effects via Pax8-related paralogues (Pax2 and Pax5) is ruled out, given that both transcription factors are not expressed in thyroid cells.
Regarding the comparison of siPax8-PCCl3 vs. wt PCCl3, 3,035 and 3,354 probes were down and up-regulated in the Pax8-silenced condition, respectively (Additional file 5). A lower number of significant probes was detected for siPax8-PCCl3 vs. siScramble-PCCl3 (797 and 777 probes were down and up-regulated in the Pax8-silenced condition, respectively) (Additional file 5). Statistically significantly differently expressed probes (adjusted p-values <0.005) for both comparisons included 633 down and 565 up-regulated targets (Additional file 5), which represent a set of 849 loci.
Pax8 is involved in controlling key cellular events
FatiScan gene set enrichment analysis
Gene Ontology term
WT vs Pax8
Scramble vs Pax8
Response to external stimulus (GO:0009605)
Response to wounding (GO:0009611)
Cellular component movement (GO:0006928)
Response to hormone stimulus (GO:0009725)
Immune response (GO:0006955)
Cell adhesion (GO:0007155)
Response to steroid hormone stimulus (GO:0048545)
Antigen processing and presentation (GO:0019882)
Cell migration (GO:0016477)
Single functional analysis
We additionally used the FatiGO in silico tool to extract Gene Ontology (GO) terms overrepresented in our down- and up-regulated set of differentially expressed genes. Considering down-regulated probes for each comparison, we observed an enrichment in biological processes related to a wide variety of DNA, RNA, and protein processes (purine and pyrimidine metabolism, response to DNA damage, DNA replication, nucleotide and base exchange repair, mismatch repair and homologous recombination, RNA degradation, and amino acid metabolism), cell response to chemical and stress stimuli, immune response, and p53 and insulin-related pathways (phosphatidyl inositol system and metabolism) (Additional file 9). Concerning GO terms enriched amongst up-regulated probes, it is worth to mention the over-representation of genes involved in biological processes such as immune response, cell response to stimuli, apoptosis and cell death, cell motion/migration/adhesion, and regulation of cell differentiation (Additional file 10).
KEGG pathways associated to Pax8 silencing
Scr. vs Pax8
Wt. vs Pax8
Phosphatidylinositol signaling system
Inositol phosphate metab.
Glycine, serine and threonine metab.
Selenoamino acid metab.
Cysteine and methionine metab.
Arginine and proline metab.
Cell adhesion molecules
Antigen processing and presentation
Autoimmune thyroid disease
Base excision repair
Nucleotide excision repair
p53 signaling pathway
Cell adhesion molecules
Cytosolic DNA- sensing pathway
NOD-like receptor signaling pathway
Toll-like receptor signaling pathway
Chemokine signaling pathway
Renal cell carcinoma
Pathways in cancer
Autoimmune thyroid disease
Antigen processing and presentation
Integrated data reveal a reduced percentage of genes transcriptionally regulated through promoter sequences
Independent validation confirms significant findings defined by ChIP-seq and expression arrays
In addition, Pax8 silencing by means of transient transfection of siRNA was significantly associated with decreased expression levels of these potential targets (Figure 7B, upper pannel), thus demonstrating a direct transcriptional effect of Pax8 on these genes. mRNA expression validation was also done for several genes that were upregulated in the absence of Pax8, including the genes encoding: CCL2, a chemokine involved in thyroid autoimmunity ; S100A4, a calcium-binding protein which plays a role in angiogenesis, extracellular matrix remodelling and tumor microenvironment, and reported to be overexpressed in metastatic papillary thyroid microcarcinomas ; SCNN1G and PADI1, which exert a role in Na+ transport and differentiation in epithelial cells, respectively [29, 30] (Figure 7B, lower panel). In silico analysis of significant IP peaks located along promoter areas of these loci demonstrated Pax8 potential binding sites in 3 out of 4 genes (data not shown). Globally, these findings underscore the efficiency and accuracy of ChIP-Seq and expression array technologies to define a Pax8-dependent gene network, which allowed us to identify biological functions of Pax8 in thyroid cells.
Despite the known relevance of the transcription factor Pax8 for adult thyrocyte physiology, few data have been published concerning Pax8 target genes other than key thyroid-related genes (Tg Tpo, and Nis). The transcriptional output of Pax8 during thyroid development is unknown but essential, given that thyroid follicular precursors are not formed in Pax8 null mouse embryos, which ultimately impairs the formation of follicle structures and thyroid hormone biosynthesis .
With regard to its link to tumour development, Pax8 expression decreases or is lost in follicular thyroid carcinomas as well as in oncogene-transformed thyroid cells . Moreover, several well-known tumour suppressors, including TP53 and WT1, have been defined as Pax8 targets, and cytoplasmic Pax8 staining has been positively associated with tumour size, metastasis, local invasion, recurrence, or persistence in the thyroid . Taking into account all these premises, and in order to better understand the role of Pax8 in the maintenance of thyroid function, we decided to explore the transcriptional profile of Pax8-silenced thyroid PCCl3 cells, and to integrate these signals with genome wide cis-regulatory studies. Thus, our experimental design combined putative and novel Pax8 binding sites with analysis of actual target gene expression regulation, a strategy successfully used for identifying direct targets for other transcription factors [35, 36].
Our unbiased mapping of Pax8 binding sites along the rat genome has identified a large number of DNA sequences that are occupied in living thyrocytes. Moreover, this is the first study addressing in vivo genome-wide mapping of Pax8-DNA binding sites, and the Pax8 consensus binding motif here defined encompasses motifs described by previous reports focused either on single gene regulation [7, 12] or on Paired-box DNA motif characterization [13, 14]. The ChIPSeq approach also led to significant immunoprecipitation of genomic sequences containing CpG islands, as well as CpG dinucleotides. Extensive literature has linked the location of CpG islands and GC-enriched regions to transcriptionally permissive chromatin [37, 38], which could lend support to a relevant role of Pax8 in the transcriptional output of the thyrocyte. About half of all CpG islands self-evidently contain TSSs, while the other half (known as “orphan” CpG islands) are either within or between characterized transcription units and have unknown significance [11, 38]. Despite a lack of association to annotated promoters, “orphan” CpG islands have been associated to transcriptional initiation and dynamic expression during development . In agreement with this, we found significant Pax8 binding to orphan CpG islands in intronic regions and a preferential binding to such islands 10–100 kb upstream or downstream of a transcription start site. In fact, genomic studies indicate that almost half of the human coding genes have alternative promoters  and that transcription factor binding sites (TFBSs) in classically defined promoter regions may represent a minority of genomic binding sites . Moreover, this latter report clearly demonstrated an association between TFBSs and the expression of non-coding RNAs, which could be modulating the expression of the gene encoded by the opposite strand. Less directly, a subset of intergenic H3K4me3 peaks, many of which are likely to correspond to orphan CpG islands, were found to represent TSSs for long non-coding RNAs . Our findings suggest that Pax8 binds orphan CpG islands that could represent alternative promoters of nearby annotated genes  or ncRNAs that regulate gene expression.
Otherwise, Pax8-dependent ChIP-Seq data demonstrated an enrichment of genomic regions with overrepresentation of general transcriptional regulatory elements (Human MTE and Drosophila MTE, Inr-DPE and BRE). MTE constitutes a core promoter element (~20-30 nt downstream of the TSS) associated with RNA polymerase II-mediated transcription [44, 45]. Furthermore, human orphan CpG islands have been associated with RNA polymerase II binding sites . On the other hand, Inr-DPE and BRE elements represent functional binding sites for TFIIB and TFIID (transcription initiation factor IIB and IID, respectively), which are main components of the basal transcription machinery . Interestingly, Jin et al recently described synergistic MTE-Inr-BRE transcriptional modules in more than 9,000 orthologous mouse and human genes . Whereas functional experiments should be performed to demonstrate an interaction of Pax8 with these general core elements, our data underscore the importance of synergistic interactions between core promoter elements and tissue-specific TFs to ultimately modulate gene expression.
Potential Pax8 partners in transcriptional regulation
2Apart from the classical view of TFs interacting with promoter regions, TFs could activate gene expression by interacting with common lineage-specific TFs and/or binding to distal regions (enhancers). Synergistic effects of Pax8 and AP1 proteins have been shown to occur in the regulation of Nis transcription through interaction along the NUE element , and AP1 and PAX proteins also interact to cooperate in the modulation of transcription of other genes . Accordingly, we observed an overrepresentation of binding motifs related to NRF-1 (Nuclear respiratory factor-1), and several AP1 members (c-FOS, BATF3, and c-JUN) were differentially expressed in Pax8-deprived thyroid cells. However, no significant findings were obtained for other transcription factors described to act synergistically with Pax8, such as Nkx2-1 and TAZ/WWTR1 proteins , indicating that this cooperative transcriptional role could be restricted to specific loci rather than representing a global transcription phenomenon in thyroid cells.
Functional studies described in the present paper confirmed physical in vivo interactions between Pax8 and CTCF or Sp1 in thyrocytes. These novel partners were further demonstrated to modulate the effect of Pax8 on the transcription of the NIS gene, thus confirming that these interactions are functionally relevant. Evidence has been accumulating concerning the role of CTCF in the establishment of intra-chromosomal loops which ultimately mediate protein-protein contacts between distal complexes and the general transcription machinery [49, 50]. On the other hand, Sp1 is a ubiquitously expressed transactivator, which physically interacts with several components of TFIIB and TFIID (mentioned above as potential Pax8 interacting proteins) and factors related to epigenetic events, such as histone deacetylases and p300/CBP histone acetyltransferase . Interestingly, several studies have described synergistic interactions between Pax8 and p300 acetyltransferase for enhancing the transcriptional activity of thyroid-related genes [52, 53]. Taking into account this complete transcriptional scenario, our data describe potential interactions of Pax8 with both common TFs and core elements, which could cooperate in chromatin remodeling for transcriptional regulation in thyroid cells.
Identification of biological processes controlled by Pax8 in thyroid cells
Pax8 has been mainly associated to thyroid differentiation and development through its transcriptional role in key thyroid-related genes [54, 55]. At this regard, we observed a downregulation of DIO1 after abolishing Pax8 (Additional file 5), which potentially binds to a critical region for selenocystein insertion in the DIO1 mRNA. Data were recently provided indicating that TSH tightly regulates DIO1 expression in thyroid cells through Pax8-dependent DIO1 mRNA stabilization (S.G. Leoni; unpublished observations). Moreover, gene expression profiling in normal versus malignant thyroid tissues demonstrated a downregulation of DIO1 and DIO2 , which could be linked to Pax8 loss during cancer progression.
Intriguingly, Pax8 modulates the expression of several genes involved in carcinogenesis and thyroid malignancies (phosphatidyl-inositol/insulin and MAPK pathways) and cell cycle processes (CDKN2B CCNB1 and CCNB2, among others) (Additional file 11). These findings are in accordance with previous studies in which Pax8 expression was abolished in the differentiated thyroid cell line FRTL5 [20, 57]. Our data would also explain the biological mechanism underlying the partial decrease in thyrocyte proliferation in response to both IGF-I and TSH (main regulators of thyroid proliferation and differentiation) after both Nkx2.1 and Pax8 mRNA silencing .
DNA-related biological processes involved a plethora of functional categories (replication, repair and metabolism), highlighting the novel finding of Brca1-dependence on Pax8. In this regard, Shih et al described that BRCA1 and BRCA2 germline mutations were twice as common in individuals developing a second non-ovarian carcinoma, with follicular thyroid carcinoma being one of the most frequent secondary tumours . This finding can be of great relevance in the development of sporadic thyroid tumors, given that, as mentioned before, Pax8 expression is decreased or lost in thyroid tumours.
Recent reports have associated the transcription factors Pax2 and Pax5 with increased capabilities for cell motility and adhesion in human cancer [58, 59]. In parallel with these Pax-related functions, we observed significant expression changes of loci involved in cell motion/adhesion, notably the Pax8 effect on NCAM1 (neural cell adhesion molecule 1) transcription. NCAM1 and other components of adherens junctions, such as cadherins, have been described to be essential for maintaining cell polarity and epithelial integrity . Interestingly, Cadherin-16 (Cdh16/Ksp-cadherin) was recently proposed to play a TSH-regulated role in thyroid development , and its expression and promoter activity is controlled by Pax8 [20, 62]. We have not only confirmed transcriptional regulation of Cdh16 by PAX8, but also defined additional PAX8-dependent genes that could be essential for thyroid cell polarity (MYO5b and Rab17, among others). In this regard, germline mutations in MYO5b have been associated with disruption of epithelial cell polarity in MVID (MIM251850) . This role is exerted via its involvement in vesicle trafficking through direct interactions with Rab GTPase proteins, such as RAB11a and RAB8a. Further functional studies should be performed to evaluate potential Myo5b interactions with RAB17, another Rab GTPase protein involved in membrane trafficking and confirmed as a Pax8 target in the present study.
State-of-the-art cis-regulatory sequencing studies have been combined with mRNA silencing and expression arrays to further characterize the functional relevance of TF-interacting DNA regions and thus to define their transcriptional output. In our study, we describe Pax8 as a master regulator of key cellular processes for thyrocyte biology, including cell cycle regulation, DNA repair, replication and metabolism, and cell polarity, and define a large set of genes whose expression is modulated by Pax8. However, only a minor fraction (6.4%) of the Pax8 binding sites identified are close to TSSs and correlate with altered mRNA expression, in agreement with studies carried out on other TFSs (1-10%) [35, 36]. This moderate percentage may be explained by the Pax8 binding site distribution, where most of the binding sites are related with orphan CGI regions. In this regard, our study demonstrates Pax8 binding sites in regions distal to TSSs, preferentially in intronic regions, which highlights a potential role as a distal or alternative transcriptional regulator, although this does not rule out indirect regulation. Distal regulation by Pax8 is supported by the interaction with chromatin remodeling factors such as CTCF and Sp1 described in the present study. Therefore, these findings suggest a new function of Pax8 as a chromatin remodeling factor in thyroid follicullar cells, which should be validated and elucidated in future studies.
Cell culture and plasmids
PCCl3 cells are a continuous line of thyroid follicular cells derived from Fischer rats that express the thyroid-specific genes Tg Tpo, and Nis, as well as the thyroid-specific transcription factors Nkx2.1, Foxe1, and Pax8 . They were grown in Coon’s modified Ham’s F-12 medium supplemented with 5% donor calf serum and a six-hormone mixture . For transfection assays, HeLa cells were used and cultured as described .
The 2,854-bp DNA fragment of the rat Nis promoter (pNIS-2.8) which contains the NUE region with two Pax8 binding sites was cloned in our laboratory . Full length Pax8, Sp1, and CTCF were subcloned respectively in pcDNA3.1+, pBS and pcDNA1 Neo, and have been previously described [66–68].
ChIP samples were prepared from PCCl3 cells as follows: cultures of 10 × 106 cells were cross-linked with 1% formaldehyde for 10 minutes at room temperature. Cross-linking was stopped by the addition of glycine to a final concentration of 125 mM, and cells were washed twice with PBS. The cell pellet was resuspended consecutively in ChIP lysis buffers  and sonicated for 90 minutes (30 seconds high frequency pulsing followed by 30 seconds resting) using the Bioruptor sonicator (Diagenode, Denville, NJ) to produce chromatin fragments of 200–500 bp on average. After isolating the sheared chromatin, we incubated it with Pax8 antibody-coated magnetic beads. To prepare these beads, 100 μl of magnetic sheep anti-rabbit IgG beads (Invitrogen, Carlsbad, CA) were incubated overnight with 10 μg polyclonal anti-mouse Pax8 antibody (Biopat, Milan, Italy), that recognizes also rat Pax8 at 4°C. The following day, the beads were rinsed and added to the sheared chromatin and incubated overnight at 4°C. Samples were then rinsed five times with RIPA buffer, and the antibody was stripped from the beads by incubating in 1% SDS at 65°C for 15 minutes; cross-linking was reversed by incubating overnight at 65°C. The next day, samples were sequentially treated with RNAse A and Proteinase K, phenol-chloroform extracted, ethanol precipitated in the presence of 20 μg glycogen, and resuspended in 50 μl 10 mM Tris pH 8.0. Procedure controls included an input condition, obtained before DNA-protein complex sonication and further used during ChIP-Seq assays as normalization sample, and non-immunoprecipitated DNA (non-IP DNA), which was obtained just prior to Pax8 immunoprecipitation.
Before sequencing, Pax8-IP DNA (IP) was used to confirm enrichment of target DNA fragments (Additional file 13) by means of real time-PCR, using as positive IP controls both the Nis upstream enhancer element (NUE) and Tpo promoter sequences [7, 9]. Negative controls of Pax8 binding to genomic DNA included promoter areas of Gad1 (glutamate decarboxylase 1) and Afm (afamin or alpha-albumin), and a region of the Nis locus that does not bind Pax8. PCR reactions were assembled in triplicate with SYBR Green ER qPCR Supermix (Invitrogen, Carlsbad, CA) and run on an Applied Biosystem 7500 Real Time PCR system. The enrichment of target sequences in ChIP material was calculated relative to the Afm negative control, and normalized to their relative amplification in non-IP DNA.
Illumina high-throughput sequencing
After verifying Pax8 target enrichment, IP and non-IP DNAs were modified for sequencing following the ChIP-Seq manufacturer’s protocol (Illumina, San Diego, CA). Briefly, DNAs were blunted with a combination of T4 DNA polymerase, Klenow polymerase, and T4 PNK. Then, a single 3′-end “A” base was added using Klenow exo (3′-to-5′ exo minus). Adapters provided by Illumina were ligated to the ends of the modified DNA before size selection of 200-bp fragments via polyacrylamide gel electrophoresis followed by extraction. The isolated DNA samples were used as the template for amplification by 18 cycles of PCR, and used for cluster generation on the Illumina Genome Analyzer II. Amplified products were column-purified with the QIAquick PCR Purification Kit (Qiagen, Dusseldorf, Germany) and assayed for quantity and quality with the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA).
The 50 bp sequence reads were aligned to the rat genome (rn4; NCBI build 4) using the MIRO pipeline (Centre for Genomic Regulation, Barcelona, Spain) allowing 2 mismatches, and aligned tags were converted to BED format and used for identification of binding sites. In order to visualize the data in the University of California Santa Cruz genome browser (http://genome.ucsc.edu), the sequence reads were directionally extended to 300 bp, and for each base pair in the genome the number of overlapping sequence reads was determined and averaged over a 10 bp window. All sequencing data can be downloaded from Gene Expression Omnibus (GEO) under accession number GSE26938.
Peak finding and data analysis
MACS program (Model-based Analysis for ChIP-Seq, v.1.4.1) was used with default parameters to determine enriched Pax8 binding regions using non-IP DNA as control. PeakAnalyzer software  was assessed to identify functional elements proximal to the immunoprecipitated peaks using the annotation of the Ensembl release 63  on the RGSC genome assembly v3.4.
The distance correlation analysis was done with the GenomeInspector tool of the Genomatix suite (Genomatix Software GmbH, Munich, Germany), within +/−10Kb from the middle of the CpG islands and simple nucleotide repeats. CpG islands and simple nucleotide repeat coordinates were obtained from the UCSC Genome Browser .
We used two approaches for motif search in the Pax8 binding sites defined by MACS. The first method, based on MEME-ChIP  and focusing on the central 100 bp portion of each sequence, was used for the 500 peaks with the best FDR. The TOMTOM program was used to compare known transcriptional motifs with the motifs identified by MEME-ChIP . On the other hand, the RegionMiner tool of the Genomatix suite (Genomatix Software GmbH, Munich, Germany) identified the most over-represented motifs, based on the background of occurrences of the transcription factor binding sites (TFBSs) within the whole sequence of the rat genome (rn4; NCBI build 4); we compared these to the Pax8 binding regions identified by MACS. The motifs were ranked by the Z-score/fold change to obtain the most relevant sites .
Polyclonal antibodies (1 μg) were bound to Dynabeads (Invitrogen, Carlsbad, CA) and incubated with 200 μg of nuclear proteins extracted as described  from PCCl3 thyroid cells. The incubation was performed in 300ul of Immunoprecipitation (IP) buffer (20 mM HEPES pH 8, 10 mM KCl, 0,15 mM EGTA, 0,15 mM EDTA, 150 mM NaCl, 0.1% NP-40 with a cocktail of protease inhibitors (Roche, Manhein Germany)). After washing with IP buffer, proteins were eluted in 20 μl of Laemmli sample buffer and boiled for 10 minutes. The immunocomplexes were analyzed by SDS-PAGE and then immunoblotted using anti-Pax8 (BioPat, Milan Italy) and anti-Sp1 (Santa Cruz Biotechnology Inc., Santa Cruz, CA) antibodies. In the case of CTCF and prior to CoIP, we transfected into PCCl3 cells an expression vector containing the full-length human CTCF, as the antibody used (Upstate Biotechnology, Waltham, MASS) recognized the human form more specifically.
Promoter activity assays
HeLa cells were transiently transfected using calcium phosphate with 1 μg of pNIS-2.8 reporter alone or in combination with 0.5 μg of expression vectors for Pax8, Sp1 and CTCF as indicated in the text. The Renilla luciferase-encoding pRL-CMV vector (50 ng) was used to correct for transfection efficiency. Forty-eight hours after transfection cells were harvested, lysed, and analyzed for firefly and renilla luciferase activities by the Dual-Luciferase reporter assay system (Promega, Madison WI). Promoter activity was determined as the ratio between firefly and renilla luciferase and represented as relative luciferase activity. The results were expressed as the mean ± SD of three independent experiments, each performed in triplicate. Data were analyzed with GraphPad Prism (Intuitive Software for Science, San Diego, CA). Statistical significance was determined using an Anova one-way test, and differences were considered significant at a P < 0.05.
The Pax8-dependent gene expression study was performed in differentiated PCCl3 thyroid cells by means of expression arrays (Agilent rat whole genome 44 K arrays). For this purpose, we generated three different conditions to finally establish two main comparisons: wild type vs. Pax8-silenced PCCl3 cells (siPax8 PCCl3), and scrambled siRNA-treated (siScramble PCCl3) vs. Pax8-silenced PCCl3 cells. Given that each comparison was performed using quadruplicates and dye-swaps (Cy3 and Cy5 fluorochromes), our experimental design included sixteen independent competitive hybridizations (Additional file 14).
Transient transfections of PCCl3 cells were performed using Lipofectamine 2000 (Invitrogen, Carlsbad, CA), both for scrambled and for Pax8 siRNA conditions (10 ng siRNA /ml) (Dharmacon, Denver, USA). Pax8 silencing was tested by means of western blotting using a polyclonal Pax8 mouse antibody (Biopat, Milan, Italy) at different time points (24 and 48 hours) after transfection (Additional file 15). Once the 48 hours condition was defined as the best time point for Pax8 silencing, we performed additional transfections to isolate total RNA using TRIzol reagent (Invitrogen, Carlsbad, CA) for each condition considered (siPax8, scrambled siRNA and PCCl3 cells treated with lipofectamine) following the manufacturer’s recommended protocol. RNA quality was evaluated with the Agilent 2100 Bioanalyzer and later amplified and labelled by using the Low RNA Input Linear Amplification Kit PLUS, Two-Color (Agilent Technologies, Palo Alto, CA). Briefly, for each sample 2 μg of total input RNA were amplified in two rounds of amplification following the manufacturer’s instructions. First strand cDNA synthesis and amplification reactions were carried out using random and T7 primers, respectively. During the 2-hour in vitro transcription, Cy3- or Cy5-labeled CTP was incorporated into each amplified RNA (cRNA). Products of the reaction were then purified using RNAeasy mini spin columns (Qiagen, Dusseldorf, Germany). Hybridization and slide and image processing were carried out according to the manufacturer’s instructions (Two-Color Microarray-Based Gene Expression Analysis protocol). In each experiment, 825 ng of contrasting cRNA samples were fragmented at 60°C for 30 min and hybridized at 65°C for 17 hr. The slides were scanned at a 10 μm resolution using the Agilent G2565BA Microarray Scanner (Agilent Technologies, Palo Alto, CA). Signal quantification was carried out with Feature Extraction 9.1 software (Agilent Technologies, Palo Alto, CA), using default analysis parameters for Agilent’s whole rat genome 44 K gene expression arrays. Array data were normalized using loess and quantile methods for normalization within and between arrays, respectively. Differential expression analysis was done using Bioconductor’s limma package. At a later stage, we used the annotate package and the data base rgug4131a.db to obtain the annotations of the rat genome from Agilent. Genes that showed adjusted p-values <0.005 were considered differentially expressed both in wild type vs. siPax8 cells and in siScramble PCCl3 vs. siPax8 PCCl3 cells. Functional analysis of Gene Ontology (GO) terms was carried out using the FatiGO tool and gene set enrichment analysis was performed using FatiScan [76, 77]. All microarray data can be downloaded from the Gene Expression Omnibus (GEO) under accession number GSE26938.
Experimental validation for ChIP-seq and expression array data
Technical validations were performed by means of real-time PCR to verify the Pax8-dependency of 7 loci, which showed significant results for both expression profiling and ChIP-Seq, independently of the peak location along the considered gene. After performing an independent Pax8-chromatin IP, we obtained genomic DNA from IP, non-IP, and input samples, which were further used to amplify specific fragments contained in IP peaks (Additional file 13). The immunoprecipitation ratio for IP peaks was estimated comparing IP versus non-IP amplification values using as normalizing regions those mentioned above (Gad1 and Afm), which were confirmed as negative controls by the ChIP-Seq results.
siRNA transfection was done to obtain cDNA for each of the three conditions initially considered for expression profiling (Pax8 siRNA, scrambled siRNA, and wild type PCCl3 cells). Expression level changes were defined in 7 down-regulated genes and in 4 up-regulated genes by means of real-time PCR for fragments specifically amplifying transcripts of interest (Additional file 16), using GAPDH as a control for target gene expression normalization.
Public database accesion number
Sequencing and gene expression microarray data have been deposited in the GEO database (accession number GSE26938).
Chromatin immunoprecipitation followed by massive sequencing
Model-based Analysis for ChIP-Seq
We thank Dr. Vassart (Université Libre de Bruxelles, Brussels, Belgium), Dr. Angel Pascual (Instituto Investigaciones Biomédicas, Madrid Spain) and Dr. Colin Goding (Ludwig Institute for Cancer Research, UK) for kindly providing the Pax8, Sp1 and CTCF expression vectors, respectively, and Dr. Ronald Hartong for his criticisms and linguistic assistance.
We acknowledge the support of Grants BFU-2010-16025 from the Dirección General de Proyectos de Investigación; RD06/0020/0060 from FIS, Instituto de Salud Carlos III, and S2011/BMD-2328 TIRONET project from the Comunidad de Madrid (Spain).
S. Ruiz-Llorente holds a postdoctoral fellowship of the Instituto de Salud Carlos III (Contrato Postdoctoral de Perfeccionamiento; CD05-0055). A. Sastre-Perona holds a predoctoral fellowship from the Formación Personal Universitario (FPU) program. C. Montero-Conde holds a postdoctoral fellowship of the Spanish Ministry of Science and Innovation (MICINN; BMED2008-0659).
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