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RNA sequencing of Sleeping Beauty transposon-induced tumors detects transposon-RNA fusions in forward genetic cancer screens.

ABSTRACT: Forward genetic screens using Sleeping Beauty (SB)-mobilized T2/Onc transposons have been used to identify common insertion sites (CISs) associated with tumor formation. Recurrent sites of transposon insertion are commonly identified using ligation-mediated PCR (LM-PCR). Here, we use RNA sequencing (RNA-seq) data to directly identify transcriptional events mediated by T2/Onc. Surprisingly, the majority (?80%) of LM-PCR identified junction fragments do not lead to observable changes in RNA transcripts. However, in CIS regions, direct transcriptional effects of transposon insertions are observed. We developed an automated method to systematically identify T2/Onc-genome RNA fusion sequences in RNA-seq data. RNA fusion-based CISs were identified corresponding to both DNA-based CISs (Cdkn2a, Mycl1, Nf2, Pten, Sema6d, and Rere) and additional regions strongly associated with cancer that were not observed by LM-PCR (Myc, Akt1, Pth, Csf1r, Fgfr2, Wisp1, Map3k5, and Map4k3). In addition to calculating recurrent CISs, we also present complementary methods to identify potential driver events via determination of strongly supported fusions and fusions with large transcript level changes in the absence of multitumor recurrence. These methods independently identify CIS regions and also point to cancer-associated genes like Braf. We anticipate RNA-seq analyses of tumors from forward genetic screens will become an efficient tool to identify causal events.

SUBMITTER: Temiz NA

PROVIDER: S-EPMC4691744 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

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RNA sequencing of Sleeping Beauty transposon-induced tumors detects transposon-RNA fusions in forward genetic cancer screens.

Temiz Nuri A NA Moriarity Branden S BS Wolf Natalie K NK Riordan Jesse D JD Dupuy Adam J AJ Largaespada David A DA Sarver Aaron L AL

Genome research 20151109 1

Forward genetic screens using Sleeping Beauty (SB)-mobilized T2/Onc transposons have been used to identify common insertion sites (CISs) associated with tumor formation. Recurrent sites of transposon insertion are commonly identified using ligation-mediated PCR (LM-PCR). Here, we use RNA sequencing (RNA-seq) data to directly identify transcriptional events mediated by T2/Onc. Surprisingly, the majority (∼80%) of LM-PCR identified junction fragments do not lead to observable changes in RNA transc ...[more]

PMID: 26553456

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Project description:BackgroundAnimal models of cancer are useful to generate complementary datasets for comparison to human tumor data. Insertional mutagenesis screens, such as those utilizing the Sleeping Beauty (SB) transposon system, provide a model that recapitulates the spontaneous development and progression of human disease. This approach has been widely used to model a variety of cancers in mice. Comprehensive mutation profiles are generated for individual tumors through amplification of transposon insertion sites followed by high-throughput sequencing. Subsequent statistical analyses identify common insertion sites (CISs), which are predicted to be functionally involved in tumorigenesis. Current methods utilized for SB insertion site analysis have some significant limitations. For one, they do not account for transposon footprints - a class of mutation generated following transposon remobilization. Existing methods also discard quantitative sequence data due to uncertainty regarding the extent to which it accurately reflects mutation abundance within a heterogeneous tumor. Additionally, computational analyses generally assume that all potential insertion sites have an equal probability of being detected under non-selective conditions, an assumption without sufficient relevant data. The goal of our study was to address these potential confounding factors in order to enhance functional interpretation of insertion site data from tumors.ResultsWe describe here a novel method to detect footprints generated by transposon remobilization, which revealed minimal evidence of positive selection in tumors. We also present extensive characterization data demonstrating an ability to reproducibly assign semi-quantitative information to individual insertion sites within a tumor sample. Finally, we identify apparent biases for detection of inserted transposons in several genomic regions that may lead to the identification of false positive CISs.ConclusionThe information we provide can be used to refine analyses of data from insertional mutagenesis screens, improving functional interpretation of results and facilitating the identification of genes important in cancer development and progression.

Dataset Information

RNA sequencing of Sleeping Beauty transposon-induced tumors detects transposon-RNA fusions in forward genetic cancer screens.

Publications

RNA sequencing of Sleeping Beauty transposon-induced tumors detects transposon-RNA fusions in forward genetic cancer screens.

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