ArticleNucleic acids research2012
New methods for finding common insertion sites and co-occurring common insertion sites in transposon- and virus-based genetic screens.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 22 citations in OpenAlex.
- LITAF protects against pore-forming protein-induced cell death by promoting membrane repair.Science immunology · 2024Article
- Transmicron: accurate prediction of insertion probabilities improves detection of cancer driver genes from transposon mutagenesis screens.Nucleic acids research · 2023Article
- SB Digestor: a tailored driver gene identification tool for dissecting heterogeneous Sleeping Beauty transposon-induced tumors.International journal of biological sciences · 2023Article
- MHC class II transactivator CIITA induces cell resistance to Ebola virus and SARS-like coronaviruses.Science (New York, N.Y.) · 2020Article
- Sleeping Beauty Mouse Models of Cancer: Microenvironmental Influences on Cancer Genetics.Frontiers in oncology · 2019Review
- SB Driver Analysis: a Sleeping Beauty cancer driver analysis framework for identifying and prioritizing experimentally actionable oncogenes and tumor suppressors.Nucleic acids research · 2018Article
- Vector Integration Sites Identification for Gene-Trap Screening in Mammalian Haploid Cells.Scientific reports · 2017Article
- Genome-wide transposon screening and quantitative insertion site sequencing for cancer gene discovery in mice.Nature protocols · 2017Article
- A Graph Based Framework to Model Virus Integration Sites.Computational and structural biotechnology journal · 2016Article
- The utility of transposon mutagenesis for cancer studies in the era of genome editing.Genome biology · 2015Review
- Transposon Mutagenesis Screen Identifies Potential Lung Cancer Drivers and CUL3 as a Tumor Suppressor.Molecular cancer research : MCR · 2015Article
- Sequencing methods and datasets to improve functional interpretation of sleeping beauty mutagenesis screens.BMC genomics · 2014Article
- Chromatin landscapes of retroviral and transposon integration profiles.PLoS genetics · 2014Article
- Evaluating risks of insertional mutagenesis by DNA transposons in gene therapy.Translational research : the journal of laboratory and clinical medicine · 2013Review
- Identification of Sleeping Beauty transposon insertions in solid tumors using linker-mediated PCR.Journal of visualized experiments : JoVE · 2013Article
- TAPDANCE: an automated tool to identify and annotate transposon insertion CISs and associations between CISs from next generation sequence data.BMC bioinformatics · 2012Article
- Applications of DNA integrating elements: Facing the bias bully.Mobile genetic elementsReview
Corrections and comments
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Authors and funding
9 authors at 7 institutions in 4 countries.
Funding
Abstract
Insertional mutagenesis screens in mice are used to identify individual genes that drive tumor formation. In these screens, candidate cancer genes are identified if their genomic location is proximal to a common insertion site (CIS) defined by high rates of transposon or retroviral insertions in a given genomic window. In this article, we describe a new method for defining CISs based on a Poisson distribution, the Poisson Regression Insertion Model, and show that this new method is an improvement over previously described methods. We also describe a modification of the method that can identify pairs and higher orders of co-occurring common insertion sites. We apply these methods to two data sets, one generated in a transposon-based screen for gastrointestinal tract cancer genes and another based on the set of retroviral insertions in the Retroviral Tagged Cancer Gene Database. We show that the new methods identify more relevant candidate genes and candidate gene pairs than found using previous methods. Identification of the biologically relevant set of mutations that occur in a single cell and cause tumor progression will aid in the rational design of single and combinatorial therapies in the upcoming age of personalized cancer therapy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.