Genome-wide transposon screening and quantitative insertion site sequencing for cancer gene discovery in mice


Transposon-mediated forward genetics screening in mice has emerged as a powerful tool for cancer gene discovery. It pinpoints cancer drivers that are difficult to find with other approaches, thus complementing the sequencing-based census of human cancer genes. We describe here a large series of mouse lines for insertional mutagenesis that are compatible with two transposon systems, PiggyBac and Sleeping Beauty, and give guidance on the use of different engineered transposon variants for constitutive or tissue-specific cancer gene discovery screening. We also describe a method for semiquantitative transposon insertion site sequencing (QiSeq). The QiSeq library preparation protocol exploits acoustic DNA fragmentation to reduce bias inherent to widely used restriction–digestion-based approaches for ligation-mediated insertion site amplification. Extensive multiplexing in combination with next-generation sequencing allows affordable ultra-deep transposon insertion site recovery in high-throughput formats within 1 week. Finally, we describe principles of data analysis and interpretation for obtaining insights into cancer gene function and genetic tumor evolution.

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Figure 1: Natural autonomous transposons and nonautonomous two-component systems engineered for insertional mutagenesis in mice.
Figure 2: A versatile platform of mouse models for insertional mutagenesis.
Figure 3: Mechanisms of ATP transposon–mediated mutagenesis.
Figure 4: Library preparation for QiSeq.
Figure 5: DNA fragmentation methods for splinkerette PCR: restriction digestion versus acoustic shearing.
Figure 6: Transposon insertion sites identified by QiSeq.

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  1. 1

    Kool, J. & Berns, A. High-throughput insertional mutagenesis screens in mice to identify oncogenic networks. Nat. Rev. Cancer 9, 389–399 (2009).

    CAS  Article  Google Scholar 

  2. 2

    St Johnston, D. The art and design of genetic screens: Drosophila melanogaster. Nat. Rev. Genet. 3, 176–188 (2002).

    CAS  Article  Google Scholar 

  3. 3

    Bessereau, J.-L. Transposons in C. elegans. WormBook 1–13 (2006).

  4. 4

    Thibault, S.T. et al. A complementary transposon tool kit for Drosophila melanogaster using P and piggyBac. Nat. Genet. 36, 283–287 (2004).

    CAS  Article  Google Scholar 

  5. 5

    Ivics, Z., Hackett, P.B., Plasterk, R.H. & Izsvák, Z. Molecular reconstruction of Sleeping Beauty, a Tc1-like transposon from fish, and its transposition in human cells. Cell 91, 501–51 (1997).

    CAS  Article  Google Scholar 

  6. 6

    Luo, G., Ivics, Z., Izsvák, Z. & Bradley, A. Chromosomal transposition of a Tc1/mariner-like element in mouse embryonic stem cells. Proc. Natl. Acad. Sci. USA 95, 10769–10773 (1998).

    CAS  Article  Google Scholar 

  7. 7

    Horie, K. et al. Efficient chromosomal transposition of a Tc1/mariner- like transposon Sleeping Beauty in mice. Proc. Natl. Acad. Sci. USA 98, 9191–9196 (2001).

    CAS  Article  Google Scholar 

  8. 8

    Fischer, S.E., Wienholds, E. & Plasterk, R.H. Regulated transposition of a fish transposon in the mouse germ line. Proc. Natl. Acad. Sci. USA 98, 6759–6764 (2001).

    CAS  Article  Google Scholar 

  9. 9

    Dupuy, A.J., Akagi, K., Largaespada, D.A., Copeland, N.G. & Jenkins, N.A. Mammalian mutagenesis using a highly mobile somatic Sleeping Beauty transposon system. Nature 436, 221–226 (2005).

    CAS  Article  Google Scholar 

  10. 10

    Collier, L.S., Carlson, C.M., Ravimohan, S., Dupuy, A.J. & Largaespada, D.A. Cancer gene discovery in solid tumours using transposon-based somatic mutagenesis in the mouse. Nature 436, 272–276 (2005).

    CAS  Article  Google Scholar 

  11. 11

    Cary, L.C. et al. Transposon mutagenesis of baculoviruses: analysis of Trichoplusia ni transposon IFP2 insertions within the FP-locus of nuclear polyhedrosis viruses. Virology 172, 156–169 (1989).

    CAS  Article  Google Scholar 

  12. 12

    Ding, S. et al. Efficient transposition of the piggyBac (PB) transposon in mammalian cells and mice. Cell 122, 473–483 (2005).

    CAS  Article  Google Scholar 

  13. 13

    Rad, R., Rad, L., Wang, W. & Cadinanos, J. PiggyBac transposon mutagenesis: a tool for cancer gene discovery in mice. Science 330, 1104–1107 (2010).

    CAS  Article  Google Scholar 

  14. 14

    Landrette, S.F. & Xu, T. Somatic genetics empowers the mouse for modeling and interrogating developmental and disease processes. PLoS Genet. 7, e1002110 (2011).

    CAS  Article  Google Scholar 

  15. 15

    Ivics, Z. et al. Transposon-mediated genome manipulation in vertebrates. Nat. Methods 6, 415–422 (2009).

    CAS  Article  Google Scholar 

  16. 16

    Wang, W. et al. Chromosomal transposition of PiggyBac in mouse embryonic stem cells. Proc. Natl. Acad. Sci. USA 105, 9290–9295 (2008).

    CAS  Article  Google Scholar 

  17. 17

    Liang, Q., Kong, J., Stalker, J. & Bradley, A. Chromosomal mobilization and reintegration of Sleeping Beauty and PiggyBac transposons. Genesis 47, 404–408 (2009).

    CAS  Article  Google Scholar 

  18. 18

    Li, M.A. et al. The piggyBac transposon displays local and distant reintegration preferences and can cause mutations at noncanonical integration sites. Mol. Cell. Biol. 33, 1317–1330 (2013).

    CAS  Article  Google Scholar 

  19. 19

    Li, M.A. et al. Mobilization of giant piggyBac transposons in the mouse genome. Nucleic Acids Res. 39, e148 (2011).

    CAS  Article  Google Scholar 

  20. 20

    Rad, R. et al. A conditional piggyBac transposition system for genetic screening in mice identifies oncogenic networks in pancreatic cancer. Nat. Genet. 47, 47–56 (2015).

    CAS  Article  Google Scholar 

  21. 21

    Dupuy, A.J. et al. A modified sleeping beauty transposon system that can be used to model a wide variety of human cancers in mice. Cancer Res. 69, 8150–8156 (2009).

    CAS  Article  Google Scholar 

  22. 22

    Starr, T., Allaei, R. & Silverstein, K. A transposon-based genetic screen in mice identifies genes altered in colorectal cancer. Science 323, 1747–1750 (2009).

    CAS  Article  Google Scholar 

  23. 23

    Vassiliou, G.S. et al. Mutant nucleophosmin and cooperating pathways drive leukemia initiation and progression in mice. Nat. Genet. 43, 470–475 (2011).

    CAS  Article  Google Scholar 

  24. 24

    Devon, R.S., Porteous, D.J. & Brookes, A.J. Splinkerettes--improved vectorettes for greater efficiency in PCR walking. Nucleic Acids Res. 23, 1644–1645 (1995).

    CAS  Article  Google Scholar 

  25. 25

    Bronner, I.F.F. et al. Quantitative Insertion-site Sequencing (QIseq) for high throughput phenotyping of transposon mutants. Genome Res. 26, 980–989 (2016).

    CAS  Article  Google Scholar 

  26. 26

    Koudijs, M.J. et al. High-throughput semiquantitative analysis of insertional mutations in heterogeneous tumors. Genome Res. 21, 2181–2189 (2011).

    CAS  Article  Google Scholar 

  27. 27

    Quail, M.A. et al. Optimal enzymes for amplifying sequencing libraries. Nat. Methods 9, 10–11 (2012).

    CAS  Article  Google Scholar 

  28. 28

    Hudson, T.J. et al. International network of cancer genome projects. Nature 464, 993–998 (2010).

    CAS  Article  Google Scholar 

  29. 29

    Stratton, M.R. Exploring the genomes of cancer cells: progress and promise. Science 331, 1553–1558 (2011).

    CAS  Article  Google Scholar 

  30. 30

    Wheeler, D.A. & Wang, L. From human genome to cancer genome: the first decade. Genome Res. 23, 1054–1062 (2013).

    CAS  Article  Google Scholar 

  31. 31

    Beroukhim, R. et al. The landscape of somatic copy-number alteration across human cancers. Nature 463, 899–905 (2010).

    CAS  Article  Google Scholar 

  32. 32

    Ellisen, L.W. et al. TAN-1, the human homolog of the Drosophila notch gene, is broken by chromosomal translocations in T lymphoblastic neoplasms. Cell 66, 649–661 (1991).

    CAS  Article  Google Scholar 

  33. 33

    Takeda, H. et al. Transposon mutagenesis identifies genes and evolutionary forces driving gastrointestinal tract tumor progression. Nat. Genet. 47, 142–150 (2015).

    CAS  Article  Google Scholar 

  34. 34

    Pérez-Mancera, P.A. et al. The deubiquitinase USP9X suppresses pancreatic ductal adenocarcinoma. Nature 486, 266–270 (2012).

    Article  Google Scholar 

  35. 35

    Mann, K.M. et al. Sleeping Beauty mutagenesis reveals cooperating mutations and pathways in pancreatic adenocarcinoma. Proc. Natl. Acad. Sci. USA 109, 5934–5941 (2012).

    CAS  Article  Google Scholar 

  36. 36

    Perna, D. et al. BRAF inhibitor resistance mediated by the AKT pathway in an oncogenic BRAF mouse melanoma model. Proc. Natl. Acad. Sci. USA 112, E536–E545 (2015).

    CAS  Article  Google Scholar 

  37. 37

    Rad, R. et al. A genetic progression model of BrafV600E-induced intestinal tumorigenesis reveals targets for therapeutic intervention. Cancer Cell 24, 15–29 (2013).

    CAS  Article  Google Scholar 

  38. 38

    Sarver, A.L., Erdman, J., Starr, T., Largaespada, D.A. & Silverstein, K.A. TAPDANCE: an automated tool to identify and annotate transposon insertion CISs and associations between CISs from next generation sequence data. BMC Bioinformatics 13, 154 (2012).

    Article  Google Scholar 

  39. 39

    McCreery, M.Q. et al. Evolution of metastasis revealed by mutational landscapes of chemically induced skin cancers. Nat. Med. 21, 1514–1520 (2015).

    CAS  Article  Google Scholar 

  40. 40

    Derse, D. et al. Human T-cell leukemia virus type 1 integration target sites in the human genome: comparison with those of other retroviruses. J. Virol. 81, 6731–6741 (2007).

    CAS  Article  Google Scholar 

  41. 41

    Mitchell, R.S. et al. Retroviral DNA integration: ASLV, HIV, and MLV show distinct target site preferences. PLoS Biol. 2, E234 (2004).

    Article  Google Scholar 

  42. 42

    Neil, J.C. & Cameron, E.R. Retroviral insertion sites and cancer: fountain of all knowledge? Cancer Cell 2, 253–255 (2002).

    CAS  Article  Google Scholar 

  43. 43

    Izsvák, Z., Ivics, Z. & Plasterk, R.H. Sleeping Beauty, a wide host-range transposon vector for genetic transformation in vertebrates. J. Mol. Biol. 302, 93–102 (2000).

    Article  Google Scholar 

  44. 44

    Yant, S.R. et al. High-resolution genome-wide mapping of transposon integration in mammals. Mol. Cell. Biol. 25, 2085–2094 (2005).

    CAS  Article  Google Scholar 

  45. 45

    Wilson, M.H., Coates, C.J. & George, A.L. PiggyBac transposon-mediated gene transfer in human cells. Mol. Ther. 15, 139–145 (2007).

    CAS  Article  Google Scholar 

  46. 46

    Mátés, L. et al. Molecular evolution of a novel hyperactive Sleeping Beauty transposase enables robust stable gene transfer in vertebrates. Nat. Genet. 41, 753–761 (2009).

    Article  Google Scholar 

  47. 47

    Yusa, K., Zhou, L., Li, M.A., Bradley, A. & Craig, N.L. A hyperactive piggyBac transposase for mammalian applications. Proc. Natl. Acad. Sci. USA 108, 1531–1536 (2011).

    CAS  Article  Google Scholar 

  48. 48

    Li, X. et al. piggyBac transposase tools for genome engineering. Proc. Natl. Acad. Sci. USA 110, E2279–E2287 (2013).

    CAS  Article  Google Scholar 

  49. 49

    Kilkenny, C., Browne, W.J., Cuthill, I.C., Emerson, M. & Altman, D.G. Improving bioscience research reporting: the ARRIVE guidelines for reporting animal research. PLoS Biol. 8, e1000412 (2010).

    Article  Google Scholar 

  50. 50

    Collier, L.S. et al. Whole-body sleeping beauty mutagenesis can cause penetrant leukemia/lymphoma and rare high-grade glioma without associated embryonic lethality. Cancer Res. 69, 8429–8437 (2009).

    CAS  Article  Google Scholar 

  51. 51

    Dorr, C. et al. Transposon mutagenesis screen identifies potential lung Cancer drivers and CUL3 as a tumor suppressor. Mol. Cancer Res. 13, 1238–1247 (2015).

    CAS  Article  Google Scholar 

  52. 52

    R Development Core Team. A Language and Environment for Statistical Computing (2008). Available online at

  53. 53

    de Ridder, J., Uren, A., Kool, J., Reinders, M. & Wessels, L. Detecting statistically significant common insertion sites in retroviral insertional mutagenesis screens. PLoS Comput. Biol. 2, e166 (2006).

    Article  Google Scholar 

  54. 54

    Mikkers, H. et al. High-throughput retroviral tagging to identify components of specific signaling pathways in cancer. Nat. Genet. 32, 153–159 (2002).

    CAS  Article  Google Scholar 

  55. 55

    Brett, B.T. et al. Novel molecular and computational methods improve the accuracy of insertion site analysis in Sleeping Beauty-induced tumors. PloS One 6, e24668 (2011).

    CAS  Article  Google Scholar 

  56. 56

    Bergemann, T.L. et al. New methods for finding common insertion sites and co-occurring common insertion sites in transposon- and virus-based genetic screens. Nucleic Acids Res. 40, 3822–3833 (2012).

    CAS  Article  Google Scholar 

  57. 57

    Akagi, K., Suzuki, T., Stephens, R.M., Jenkins, N.A. & Copeland, N.G. RTCGD: retroviral tagged cancer gene database. Nucleic Acids Res. 32, D523–D527 (2004).

    CAS  Article  Google Scholar 

  58. 58

    Abbott, K.L. et al. The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice. Nucleic Acids Res. 43, D844–D848 (2015).

    CAS  Article  Google Scholar 

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This work was supported by the Wellcome Trust, the German Cancer Consortium (DKTK), the German Research Council (SFB1243) and the Helmholtz Association (PCCC Alliance).

Author information




M.F. and R.R. wrote the manuscript. R.R., A.B., P.L., W.W., L.R., J.C., G.S.V. and A.S. designed or contributed to the development of the transposon systems in mice. M.A.Q., I.B., M.M., R.R., A.S., C.G. and G.S.V. designed or contributed to the development of QiSeq. I.B., M.M., M.F. and A.S. developed the library preparation method for plate formats. R.R., M.F., L.R., J.W., A.P., D.S., T.E. and A.B. provided and analyzed the transposon screening data. H.P., R.R. and G.S.V. developed bioinformatics tools for the analysis of insertional mutagenesis data. J.W. developed/adapted the DNA extraction protocol from formalin-fixed paraffin-embedded tissues for QiSeq.

Corresponding author

Correspondence to Roland Rad.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Read quality score per sequenced base position.

(a) Illumina Q-scores for a normal QiSeq run. Typically, more than 80% of reads reach a quality score higher than 30 across all read positions.(b) DNA extracted from formalin-fixed, paraffin embedded tissue can be sequenced to similarly high quality. (c) Samples with a low transposon mobilisation rate lead to run failure due to loss of focus; most reads consist of identical transposon transgene concatemer sequences instead of random genomic sequence. As a consequence the imaging algorithms fail, resulting in reduced quality scores for a larger fraction of reads or complete drop-outs on single base positions. (d) Spiking the library from (c) with 15% PhiX solves the problem.

Supplementary Figure 2 Mating strategies for conditional transposon screens.

(a) Setup for a tissue specific transposon screen. Transposon mice and conditional transposase mice should be kept separate until the last mating step that generates the experimental cohorts for tumour watch. Cre driver lines should be interbred with the transposon line. For details of the rationales see main text. (b) Similarly, if a sensitizing background mutation is needed, two founder cohorts are generated and maintained as indicated. The final cross produces experimental mice and all combinations of controls.

Supplementary Figure 3 Agilent Bioanalyzer QC traces

(a) Sonicated genomic DNA with a mean fragment length of 250 bp. (b) Genomic DNA after end-repair and A-tailing. Little or no peak shift should be detectable compared to (a). (c) Genomic DNA after adapter-ligation and double SPRI clean-up. Peak shift should be more than 100 bp due to adapter ligation on both ends and fragment size selection towards longer fragments due to double SPRI bead cleanup. (d) Adapter-ligated library after PCR2. Distinct subpeaks indicate amplification of transposon containing fragments over genomic-only fragments.

Supplementary Figure 4 Suggested plate layout for qPCR.

Digits are sample numbers, ‚N‘ denotes no template control, ‚S1‘ through ‚S6‘ denotes KAPA library quantification standards 1-6. Each column of the plate with the diluted library splits into 3 columns on the qPCR plate to obtain quantification in triplicate. Thus, each dilution plate requires 4 qPCR plates.

Supplementary information

Supplementary Figures and Text

Supplementary Figures 1–4, Supplementary Table 1, and the Supplementary Method. (PDF 1228 kb)

Supplementary Note 1

Custom Illumina sequencing recipe. (ZIP 10 kb)

Supplementary Note 2

A copy-and-paste template for simplified ordering of primers and oligos from IDT. (XLS 44 kb)

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Friedrich, M., Rad, L., Bronner, I. et al. Genome-wide transposon screening and quantitative insertion site sequencing for cancer gene discovery in mice. Nat Protoc 12, 289–309 (2017).

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