Abstract
The influence of local chromatin context on gene expression can be explored by integrating a transcription reporter at different locations in the genome as a sensor. Here we provide a detailed protocol for analyzing thousands of reporters integrated in parallel (TRIP) at a genome-wide level. TRIP is based on tagging each reporter with a unique barcode, which is used for independent reporter expression analysis and integration site mapping. Compared with previous methods for studying position effects, TRIP offers a 100–1,000-fold higher throughput in a faster and less-labor-intensive manner. The entire experimental protocol takes ∼42 d to complete, with high-throughput sequencing and data analysis requiring an additional ∼11 d. TRIP was developed by using transcription reporters in mouse embryonic stem (mES) cells, but because of its flexibility the method can be used to probe the influence of chromatin context on a variety of molecular processes in any transfectable cell line.
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Change history
16 January 2015
In the version of this article initially published, the final concentration of tamoxifen used in Step 53 of the Procedure was listed as 1 mM; it should be 1 µM. The error has been corrected in the HTML and PDF versions of the article.
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Acknowledgements
We thank the Netherlands Cancer Institute (NKI) Genomics Core Facility for sequencing support; the NKI Flow Cytometry Facility for fluorescence sorting support; G. Filion, A. Rosado and J.v. Arensbergen for their helpful suggestions; M. Amendola for providing the reference plasmid for IR copy number quantification; and members of our laboratories for their helpful discussions and critical reading of the manuscript. This work was supported by the Netherlands Consortium for Systems Biology (L.F.A.W., M.v.L. and B.v.S.); NWO-ALW open program grant (W.A. and M.v.L.); and EURYI, NWO-ALW VICI and European Research Council advanced grant no. 293662 (B.v.S.).
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W.A., A.V.P., M.v.L. and B.v.S. designed and developed the protocol. W.A. and A.V.P. wrote the manuscript. W.A., J.d.J. and L.P. developed the computational pipeline. J.t.H. developed the TRIP web page. M.v.L., B.v.S., L.F.A.W. and A.B. supervised the project and helped in writing.
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Integrated supplementary information
Supplementary Figure 1 Potential artifacts during the preparation of mapping samples for Illumina high-throughput sequencing.
During iPCR-based mapping, intermolecular ligations between a barcoded fragment and an unrelated fragment of DNA or between two barcoded fragments can lead to the production of fragments with non-existing combinations of barcode and the genomic DNA.
Supplementary Figure 2 Determination of average copy number of IRs in a TRIP pool.
A scheme showing different amplicons present in TRIP pools and the reference plasmid, which are used for the estimation of the average copy number of IRs per cell (see also Box 2).
Supplementary Figure 3 Structure of DNA fragments prepared for Illumina high-throughput sequencing.
(a) The structure of fragments from normalization/expression samples. (b) The structure of fragments from mapping samples.
Supplementary information
Supplementary Figure 1
Potential artifacts during the preparation of mapping samples for Illumina high-throughput sequencing. (PDF 620 kb)
Supplementary Figure 2
Determination of average copy number of IRs in a TRIP pool. (PDF 193 kb)
Supplementary Figure 3
Structure of DNA fragments prepared for Illumina high-throughput sequencing. (PDF 188 kb)
Supplementary Table 1
(PDF 76 kb)
Supplementary Table 2
(PDF 90 kb)
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Akhtar, W., Pindyurin, A., de Jong, J. et al. Using TRIP for genome-wide position effect analysis in cultured cells. Nat Protoc 9, 1255–1281 (2014). https://doi.org/10.1038/nprot.2014.072
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DOI: https://doi.org/10.1038/nprot.2014.072
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