Search tips
Search criteria 


Logo of wtpaEurope PMCEurope PMC Funders GroupSubmit a Manuscript
Science. Author manuscript; available in PMC 2013 July 23.
Published in final edited form as:
PMCID: PMC3719098

PiggyBac Transposon Mutagenesis: A Tool for Cancer Gene Discovery in Mice


Transposons are mobile DNA segments that can disrupt gene function by inserting in or near genes. Here we show that insertional mutagenesis by the PiggyBac transposon can be used for cancer gene discovery in mice. PiggyBac transposition in genetically engineered transposon/transposase mice induced cancers whose type (hematopoietic versus solid) and latency were dependent on the regulatory elements introduced into transposons. Analysis of 63 hematopoietic tumors revealed the unique qualities of PiggyBac for genome-wide mutagenesis and discovered many cancer genes not identified in previous retroviral or Sleeping Beauty transposon screens, including Spic, which encodes a PU.1-related transcription factor, and Hdac7, a histone deacetylase gene. PiggyBac and Sleeping Beauty have different integration preferences. To maximize the utility of the tool, we engineered 20 mouse lines to be compatible with both transposases in constitutive, tissue- or temporal-specific mutagenesis. Mice with different transposon types, copy numbers and chromosomal locations support wide applicability.

Genetic screening in higher organisms has been hampered for decades by the lack of efficient insertional mutagenesis tools. Retroviruses have been used for cancer gene discovery in mice, but their application has been limited to the study of hematopoietic and mammary tumors due to viral tropism for these tissues (1). DNA transposons, which are the key insertional mutagens in lower organisms, were inactivated in vertebrate genomes millions of years ago. Only recently have new transposons been engineered to be active in mammalian cells, a development that provides opportunities for their use as genetic tools in higher organisms (2). Sleeping Beauty (SB), a TC1/mariner transposon, was reconstructed from dormant elements in fish genomes and optimized to transpose in multiple cell types (3), including mouse embryonic stem cells (4). Further improvements of SB led to its successful application for somatic mutagenesis in mice (5, 6). Another transposon, PiggyBac (PB) from the cabbage looper moth, was recently engineered to be highly active in mammalian cells (7) and has been shown to have biological properties distinct from those of SB (2, 7-9). PB can move larger DNA fragments (allowing complex transgene designs to be incorporated into the transposon) and it has a weaker tendency for local hopping in vitro (which makes it an attractive candidate for genome-wide mutagenesis). Furthermore, in contrast to SB, PB does not leave undesired footprint mutations after transposition. Finally, PB and SB have different integration preferences.

To deploy PB for genetic screening in mice, we generated PB transposase knockin-mice (RosaPB) and 19 mouse lines carrying different types of transposons (Figures 1 and S1(10)). All transposons possess PB and SB inverted terminal repeats (ITRs), allowing mobilization with both transposases. Promoter/enhancer elements, a splice donor, bidirectional SV40 polyAs and two splice acceptors were introduced in between the ITRs to allow gain or loss of function mutations, depending on the transposon orientation and its spatial relation to genes. Transgenic mice were generated with three variants of these bi-functional “activating/inactivating” transposons (ATP1, ATP2, ATP3), which carry different promoter/enhancer elements (CAG, MSCV, PGK). The chromosomal location and copy number of transposons were determined for each line by FISH and qPCR (Figures S2 and S3). Nineteen transgenic mouse lines were established, with transposon arrays on 14 different chromosomes and 2 to 150 transposon copies (Figure 1).

Fig. 1
Mouse lines carrying the genetic components of the transposon systems

To analyze the biology of PB transposition in vivo, we intercrossed RosaPB mice with 14 ATP lines and assessed nearly 900 progeny. When “low copy” ATP lines (< 20 copies) were used, double-transgenic offspring were born at Mendelian frequency or close to it, whereas “high copy” ATP mice (e.g. ATP1-H39) did not produce live-born double-positive progeny (Figure 2A). Double-transgenic RosaPB;ATP1-H39 embryos were however identified, suggesting extensive transposition-induced embryonic lethality (Figure S4). Less pronounced was the effect of the transposon type and donor location on embryonic lethality, although weak positional effects could be observed for some lines (e.g. ATP1-H5). Further characteristics of PB mobilization in vivo are shown in Figure S4.

Fig. 2
Embryonic lethality, tumor spectrum and latency in different ATP mouse lines upon PiggyBac mobilization

We next investigated whether PB-based mutagenesis induced cancer in the mice. We monitored 393 animals from multiple cohorts and found that beginning at 2 months of age, double-transgenic RosaPB;ATP mice, but not single-transgenic animals, developed cancers. The tumor type and latency were profoundly influenced by the transposon type. Mobilization of ATP2 transposons resulted in highly penetrant hematopoietic cancer formation. More than 90% of RosaPB;ATP2 mice developed aggressive leukemias and lymphomas (Figure 2B and S5). In contrast, RosaPB;ATP1 animals had almost exclusively solid tumors, including sarcomas and various carcinomas with poor differentiation and metastasis (Figure 2C and S6; Tables S1 and S2).

To explore whether the lack of hematopoietic carcinogenesis in ATP1 mice is related to tissue-specificity of the CAG promoter, we generated reporter mice expressing DsRed constitutively under control of CAG from the Hprt locus. This knock-in line has two major advantages over conventional transgenic reporter mice: (i) Promoters inserted into Hprt are not subject to epigenetic silencing and drive gene expression in all tissues (11); (ii) Only one copy of the promoter/reporter is used, which accurately reflects the effect of one ATP1-CAG-transposon. The analysis of Hprt-Cag-DsRed mice revealed robust DsRed expression in most organs but not in the spleen (Figure 2E), suggesting low CAG activity in the hematopoietic compartment.

Finally, we analyzed RosaPB;ATP3 mice, which developed solid and/or hematopoietic tumors, with a high percentage of mice having both (Figure 2D and S7). Further characterization of PB-induced tumors is shown as supplementary information, including immunohistochemical subtype analysis of hematologic cancers (Figure S8), evidence for lack of generalized transposon-induced genomic instability (Figure S9), proof of clonality of insertions in tumors (Figure S10), analysis of transposase expression and transposon copy numbers in tumors (Figure S11) and the distribution pattern of different transposon types in genes (Table S3).

SB has a strong tendency for local hopping, with 32-45% of all integrations mapping to the donor chromosome in SB-induced tumors (12, 13). To examine the potential of PB for genome-wide mutagenesis, we cloned more than 50.000 transposon integration sites in 63 hematopoietic tumors originating from 3 transposon mouse lines. A total of 5,590 non-redundant insertions were identified. Figure 3 and table S4 show that PB integrations were uniformly distributed across the genome and correlated with the size and the “TTAA” frequency (the PB integration site) of individual chromosomes. There was a slightly increased insertion density on chromosomes 2, 9, 11 and 19 in all three groups of mice, which might be related to the high gene density (Table S5) or the high number of oncogenic insertions (Figure S12) on those chromosomes. On donor chromosomes the number of integrations was as expected or only slightly higher and local hopping was confined to a small region (1-3Mb) around the donor locus (Figure 3). Together these results demonstrate the unique qualities of PB for genome-wide mutagenesis.

Fig. 3
PB integration pattern in tumors from different ATP2 mouse lines

To discover candidate cancer genes, we used a statistical framework based on Gaussian Kernel convolution (14), which identified 72 unique common integration sites (CISs) at 67 independent loci (Figure 4; Table S6). Figure S12 visualizes the global transposon integration pattern for each chromosome at a 1Mb resolution and indicates all significant CIS. A search in the Retrovirus-Tagged-Cancer-Gene-Database (15) and in recent large-scale insertional mutagenesis studies (13, 16) revealed, as expected, that some of these CIS (or genes within CIS) have also been identified in earlier retroviral or SB screens (Figure 4A). Remarkably however, 42% of the CISs have not been reported before our study. Given that thousands of murine hematologic cancers have been generated and analyzed earlier using retroviral or SB mutagenesis, this high number of novel CIS was unexpected and underscores the potential of PB for genetic screening.

Figure 4
Identification of common integration sites in PiggyBac-induced hematopoietic tumors

The integration pattern in oncogenes suggests a high selective pressure for insertions in specific regions where transposons cause gene activation. All Nras or Evi1 integrations, for example, were upstream of the translation start site and transposons were sense-oriented, supporting gene expression from the unidirectional MSCV promoter (Figure 4B and S13). Some oncogenes had more complex integration patterns. Notch1, for example, had one insertion cluster in intron 27, leading to overexpression of an intracellular Notch1 domain like in human T-ALL with t(7;9) translocations (17), and a second cluster of truncating integrations in intron 2, leading to a “decoupled” intracellular domain that can be expressed from a cryptic Notch1 promoter (18).

In contrast to oncogene insertions, hits in tumor suppressor genes (TSGs) were randomly distributed throughout genes (e.g. Ikzf1 or Pten; Figure 4B) and were either sense- or antisense-oriented, suggesting that gene disruption is the disease-causing mechanism. In some tumors multiple integrations in TSGs occurred, leading to trapping of both alleles (Figure S14). Pten was frequently hit in this screen but not in previous retroviral screens, highlighting the different integration preference of these insertional mutagens.

Examples of novel candidate cancer genes with promoter insertions identified in this screen are the PU.1-related transcription factor Spic, the histone deacetylase Hdac7, the Wnt pathway component Bcl9 or the cell cycle regulatory phosphatase Cdc14 (Figure 4 and S13). Spic was hit in 9 tumors, which were all MPO-positive myeloid leukemias. In all tumors transposons were sense-oriented and located within a narrow region (760bp) upstream of the translation start site. MSCV-Spic fusion transcripts were confirmed by sequencing and Spic overexpression was shown by qRT-PCR (Figure 4C). Little is known about the biological function of Spic, but a recent study has suggested its role in myelomonocytic development (19), which further supports our findings. HDAC7 is specifically expressed in CD4/CD8-double positive human thymocytes (20), but its role in hematopoietic tumorigenesis has not been studied so far. The beta-catenin co-factor Bcl9 is a rare translocation partner in human hematopoietic malignancies (21), and a recent study revealed frequent amplifications of a chromosomal region that includes BCL9 in various human malignancies (22).

The mouse is a major model organism for the study of human physiology and disease. Our study adds an efficient and versatile tool kit for genetic screening in mice that can be exploited for a wide range of applications, including constitutive, tissue-specific or spatio-temporally controlled somatic mutagenesis using conditional and tamoxifen-inducible PB (23). In tissue-specific screens we were able to induce aggressive metastatic solid tumors, which in principle will facilitate future studies of tumor initiation, progression and metastasis, as well as the genetic basis of various histological subtypes of individual cancers. PB can be used alone for genome-wide mutagenesis, but the ATP lines described here with donor loci on 14 different chromosomes can also be used in combination with SB (e.g., to exploit its local hopping tendency (24) for chromosome-specific screens in known cancer susceptibility regions). These transposon tool kits in mice have the potential to increase the speed and efficiency with which cancer genes and oncogenic signalling networks are discovered, and should likewise facilitate functional analysis of these genes.

Supplementary Material

Supplementary Figure 1

Supplementary Figure 2

Supplemental Figure 3

Supplementary Figure 4

Supplementary Figure 5

Supplementary Figure 6

Supplementary Figure 7

Supplementary Figure 8

Supplementary Figure 9

Supplementary Figure 10

Supplementary Figure 11

Supplementary Figure 12

Supplementary Figure 13

Supplementary Figure 14

Supplementary Figure legends

Supplementary Table S1

Supplementary Table S2

Supplementary Table S3

Supplementary Table S4

Supplementary Table S5

Supplementary Table S6

Supplementary Table S7

Supplementary Data Methods

Supplementary Data References


We thank the Research support facility team, B.L. Ng, B. Fu and Y. Hooks for technical assistance; N. Carter and C. Lopez-Otin for experimental resources; L. Wessels, J. ten Hoeve and J. de Ridder for software used in data analysis and H. Prosser for reagents. The work was supported by the Wellcome Trust. R.R. and J.R. are recipients of a fellowship from the German Research Foundation and the Fundacion Maria-Cristina-Masaveu-Peterson, respectively.

Reference List

1. Kool J, Berns A. Nat. Rev. Cancer. 2009;9:389. [PubMed]
2. Ivics Z, et al. Nat. Methods. 2009;6:415. [PMC free article] [PubMed]
3. Ivics Z, Hackett PB, Plasterk RH, Izsvak Z. Cell. 1997;91:501. [PubMed]
4. Luo G, Ivics Z, Izsvak Z, Bradley A. Proc. Natl. Acad. Sci. U. S. A. 1998;95:10769. [PubMed]
5. Dupuy AJ, et al. Nature. 2005;436:221. [PubMed]
6. Collier LS, et al. Nature. 2005;436:272. [PubMed]
7. Ding S, et al. Cell. 2005;122:473. [PubMed]
8. Wang W, et al. Proc. Natl. Acad. Sci. U. S. A. 2008;105:9290. [PubMed]
9. Liang Q, Kong J, Stalker J, Bradley A. Genesis. 2009;47:404. [PubMed]
10. Supporting material available on Science online.
11. Bronson SK, et al. Proc. Natl. Acad. Sci. U. S. A. 1996;93:9067. [PubMed]
12. Starr TK, et al. Science. 2009;323:1747. [PMC free article] [PubMed]
13. Collier LS, et al. Cancer Res. 2009;69:8429. [PMC free article] [PubMed]
14. De Ridder J, et al. PLoS. Comput. Biol. 2006;2:e166. [PubMed]
15. Akagi K, et al. Nucleic Acids Res. 2004;32:D523. [PMC free article] [PubMed]
16. Uren AG, et al. Cell. 2008;133:727. [PMC free article] [PubMed]
17. Ellisen LW, et al. Cell. 1991;66:649. [PubMed]
18. Hoemann CD, et al. Mol. Cell Biol. 2000;20:3831. [PMC free article] [PubMed]
19. Kohyama M, et al. Nature. 2009;457:318. [PMC free article] [PubMed]
20. Dequiedt F, et al. Immunity. 2003;18:687. [PubMed]
21. Willis TG, et al. Blood. 1998;91:1873. [PubMed]
22. Beroukhim R, et al. Nature. 2010;463:899. [PMC free article] [PubMed]
23. Cadinanos J, Bradley A. Nucleic Acids Res. 2007;35:e87. [PMC free article] [PubMed]
24. Keng VW, et al. Nat. Methods. 2005;2:763. [PubMed]