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Supplementary Material
Materials and methods
Re-establishment of Rat1a fibroblast tumors in culture.
To re-establish Rat1a cells in in vitro culture, tumors were excised upon reaching a diameter of
ca. 1 cm, rinsed in Hank’s balanced Salt Solution (HBSS, BRL-GIBCO) and minced with
scissors in HBSS containing 0.25 mg/ml trypsin and 20 mg/ml collagenase (Sigma-Aldrich).
Following incubation for 30 min at 37C, the tissue was ticturated and passed once through a 40
M cell strainer (Becton Dickinson, Franklin Lakes, NJ). Cells were washed twice with HBSS
and either prepared directly for cell cycle analysis or plated in standard growth medium.
Immunoblotting anf immunohistochemical procedures.
Immunoblotting was performed as previously described (Rogulski et al., 2005a). Antibodies
included a murine monoclonal antibody (mAb) directed against c-Myc (9E10, Santa Cruz
Biotechnology, Inc. Santa Cruz, CA), an anti-human GpIb murine mAb (M042, Emfret
Analytics Inc. Wurzburg, Germany), an anti-p53 murine mAb (Ab-1, EMD Chemicals, Inc. San
Diego, CA), an anti p21 rabbit polyclonal antibody (H-164, Santa Cruz), anti--tubulin mAb (D10, Santa Cruz), an anti-p16INK4a mAb (F-12, Santa Cruz), and an anti -H2AX mAb (JBW301,
Upstate, Temacula, CA). Secondary antibodies included horseradish peroxidase-conjugated goat
anti-mouse IgG (Santa Cruz) for immunoblotting and Alexa FluorTM-610-conjugated goat antimouse IgG for immunofluorescence. Senescence-associated galactosidase (SA--gal) assays
were performed as previously described (Dimri et al., 1995). Chemiluminescence assays were
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performed as previously described (Li et al., 2007). DAPI staining was performed as previously
described (Rothermund et al., 2005).
Purification of RNAs and Microarray analysis.
The integrity of each RNA sample was confirmed by 1% agarose formaldehyde gel
electrophoresis followed by ethidium bromide staining and visual inspection, as well as by
analysis on an Agilent Bioanalyzer 2100 (Agilent, Palo Alto, California). 5 g of total RNA was
used as a template to generate cDNA using a T7-oligo(dT)24 primer and Superscript II reverse
transcriptase (Invitrogen, Carlsbad, CA) according to the manufacturer’s protocol. Doublestranded cDNA was synthesized in Second Strand Buffer (Invitrogen) by the addition of 10 units
T4 DNA Ligase, 40 units E. coli DNA Polymerase I, 200 M dNTPs, and 2 units RNAse H at
16C for 2 h. 10 units of T4 DNA Polymerase were then added and the reaction was continued
for an additional 5 min. Reactions were stopped by the addition of EDTA to 30 mM. Following
phenol:chloroform extraction and ethanol precipitation, an aliquot of the double-stranded cDNA
was used for the synthesis of biotinylated complementary RNA (cRNA) using a BioArray High
Yield RNA Transcript Labeling System (ENZO, Farmingdale, NY). Biotinylated cRNAs were
purified using the RNeasy Kit (Qiagen, Valencia, CA). 20 g of product was then incubated at
94C for 35 min in fragmentation buffer (40 mM Tris-acetate pH 8.1, 100 mM potassium
acetate, 30 mM magnesium acetate). 1 l of the sample was run on a 2% agarose gel to verify
that fragmentation had resulted in RNA of the desired size distribution. 15 g of fragmented
cRNA was added to 1X Hybridization Cocktail (Affymetrix, Santa Clara, CA) in a final volume
of 300 l and hybridized at 45C overnight to the Affymetrix Rat Genome 230 2.0 GeneChip.
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Washing and staining were done according to the recommendations for use of the Affymetrix
Fluidics Station.
Affymetrix GCOS v1.4 was used to extract image intensities and to normalize raw expression
data to correct for differences in signal intensities across the microarray. Expression values were
multiplied by a scaling factor to make the average intensity of the housekeeping gene set on each
microarray equal to a target intensity of 150. Independent comparative analyses for each of three
experiments were performed with Rat1a-vector and Rat1a-Gp1b diploid fluorescence data as
the baseline and experimental .cel files, respectively. This was repeated using Rat1a-vector and
Rat1a-Gp1b tetraploid fluorescence data as the baseline and experimental .cel files
respectively. Results were imported into Microsoft Excel for further analysis. Only probe sets
exhibiting a signal log2 ratio of  1.0 or  -1.0 in each of 3 replicate experiments were scored as
"Gp1b regulated". Random comparative analyses of Rat1a-vector.cel and Rat1a-Gp1b
diploid or tetraploid.cel files were performed to eliminate genes that could be regulated by
chance. Genes were ranked by net change with increased (I), decreased (D), and no change (NC)
calls assigned values of 1, 1, and 0 respectively. A net expression change (NEC) of 5 and +3
were used as the cutoffs for the diploid and tetraploid sets respectively. As a second means of
validation, Rat1a-vector.cel and Rat1a-Gp1b diploid or tetraploid.cel files were analyzed using
dChip version 1.3 software (Li and Wong, 2001). Following normalization of signal intensities
using the PM-based model, a batch comparative analysis was performed. Experimental (Rat1aGp1b diploid or tetraploid) to baseline (Rat1a-vector) ratios (E/B and B/E) of 1.2 were utilized.
A 20% filtering option was used in the Absent vs. Present call. dChip default settings were
selected for all remaining parameters. Identified gene information and accession numbers were
confirmed by BLAST search (www.ncbi.nlm.nih.gov). Genes were grouped into functional
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categories based on their known molecular and/or biological functions denoted by
http://panther.appliedbiosystems.com. Affymetrix GeneChip Operating Software Version 1.4processed comparative analysis results of the experiments have been published as supplementary
data (Supplementary Tables 1 and 2).
Supplementary Tables
Table 1. Differentially expressed transcripts in Rat1a-vector versus diploid Rat1a- GpIb cells.
Listed are the 223 differentially expressed genes identified by transcriptional profiling of the two
cell lines. To be included on the list, it was necessary for each transcript to show > or < 2-fold
differences between the cell lines in each of three replica experiments. Negative log2 signal ratios
(LSRs) indicate down-regulation of the transcript in diploid Rat1a-GpIb versus control Rat1avector cells, whereas positive LSRs indicate up-regulation of the transcript. Transcripts
highlighted in yellow identify the 60 that did not overlap with the 210 genes differentially
regulated between tetraploid Rat1a cells and control Rat1a-vector cells.
Table 2. Differentially expressed transcripts in Rat1a-vector versus tetraploid Rat1-GpIba
cells. Listed are the 210 differentially expressed genes. Criteria for listing were identical to those
described for Table 1. Transcripts highlighted in yellow identify the 47 that did not overlap with
the 224 genes differentially regulated between diploid Rat1a-GpIb cells and control Rat1avector cells.
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Table 3. Functions of tetraploid Rat1a-GpIb-specific genes. Specific functions for the 47
tetraploid-specific transcripts depicted in Figure 6d were derived from PANTHER ontology
software.
Supplementary Figures.
Figure 1. Quantification of senescence markers in HFF. (a) SA--gal quantification. The total
per cent of SA--gal positive cells from Figure 4g is depicted as an average of triplicate
determinations +/- 1S.E. At least 200 cells were counted in each sample. (b) p16INK4a
quantification. Cells were immunostained for p16INK4a as described in Figure 4h and then stained
for DAPI. The total per cent of p16INK4a-positive cells is depicted as an average of triplicate
determinations +/- 1S.E. At least 200 cells were counted in each sample. c-H2AX
quantification. Cells were immuno-stained for -H2AX as described in Figure 4i and then stained
for DAPI. The total per cent of -H2AX-positive cells is depicted as an average of triplicate
determinations +/- 1S.E. At least 200 cells were counted in each sample. Positive cells were
considered to be those with >3 foci/nucleus
Figure 2. Additional examples of abnormal nuclear morphologies observed in HFF-GpIb+p53shRNA cells. In a, the arrow points to a micronucleus. b and c show examples of multiple nuclei
of variable size either partly attached to or distinctly separate from other nuclei. D shows an
example of chromatin bridging. Scale bars = 25 m.
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Figure 3. Categorization of GpIb target genes. (a) Venn diagram of transcriptional profiles of
diploid Rat1a-GpIb versus tetraploid Rat1a-GpIb cells. In each case, cell lines were
compared to Rat1a-vector cells grown under identical conditions. Out of a total of 223
differentially expressed transcripts in diploid GpIb cells and 210 differentially expressed
transcripts in tetraploid Rat1a-GpIb cells, 163 were common, 60 were unique to diploid Rat1aGpIb cells and 47 were unique to tetraploid GpIb cells. All determinations were performed in
triplicate (See Supplementary Materials and methods). (b) Functional categorization of the 163
common genes identified in (a) above. Functions were determined using PANTHER ontology
software (http://www.pantherdb.org and Thomas et al., 2003). Only functions assignable to >5%
of transcripts in at least one of the comparisons are depicted here and in panels (b) and (b). In
cases where more than a single function or pathway was associated with a transcript, all were
included in the final analyses. (c) Functional categorization by PANTHER of the 60
differentially regulated transcripts uniquely expressed in diploid Rat1a-GpIb cells. (d)
Functional categorization by PANTHER of the 47 differentially regulated transcripts uniquely
expressed in tetraploid Rat1a-GpIb cells.
Supplementary references
Li, C. & Wong, W.H. (2001). Proc. Natl. Acad. Sci. USA 103, 31-36.
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