Dataset Information

Vector Integration Sites Identification for Gene-Trap Screening in Mammalian Haploid Cells.

ABSTRACT: Forward genetic screens using retroviral (or transposon) gene-trap vectors in a haploid genome revolutionized the investigation of molecular networks in mammals. However, the sequencing data generated by Phenotypic interrogation followed by Tag sequencing (PhiT-seq) were not well characterized. The analysis of human and mouse haploid screens allowed us to describe PhiT-seq data and to define quality control steps. Moreover, we identified several blind spots in both haploid genomes where gene-trap vectors can hardly integrate. Integration of transcriptomic data improved the performance of candidate gene identification. Furthermore, we experimented with various statistical tests to account for biological replicates in PhiT-seq and investigated the effect of normalization methods and other parameters on the performance. Finally, we developed: VISITs, a dedicated pipeline for analyzing PhiT-seq data (https://sourceforge.net/projects/visits/).

SUBMITTER: Yu J

PROVIDER: S-EPMC5356192 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Publications

Vector Integration Sites Identification for Gene-Trap Screening in Mammalian Haploid Cells.

Yu Jian J Ciaudo Constance C

Scientific reports 20170317

Forward genetic screens using retroviral (or transposon) gene-trap vectors in a haploid genome revolutionized the investigation of molecular networks in mammals. However, the sequencing data generated by Phenotypic interrogation followed by Tag sequencing (PhiT-seq) were not well characterized. The analysis of human and mouse haploid screens allowed us to describe PhiT-seq data and to define quality control steps. Moreover, we identified several blind spots in both haploid genomes where gene-tra ...[more]

PMID: 28303933

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Project description:BACKGROUND:Bioinformatics tools designed to identify lentiviral or retroviral vector insertion sites in the genome of host cells are used to address the safety and long-term efficacy of hematopoietic stem cell gene therapy applications and to study the clonal dynamics of hematopoietic reconstitution. The increasing number of gene therapy clinical trials combined with the increasing amount of Next Generation Sequencing data, aimed at identifying integration sites, require both highly accurate and efficient computational software able to correctly process "big data" in a reasonable computational time. RESULTS:Here we present VISPA2 (Vector Integration Site Parallel Analysis, version 2), the latest optimized computational pipeline for integration site identification and analysis with the following features: (1) the sequence analysis for the integration site processing is fully compliant with paired-end reads and includes a sequence quality filter before and after the alignment on the target genome; (2) an heuristic algorithm to reduce false positive integration sites at nucleotide level to reduce the impact of Polymerase Chain Reaction or trimming/alignment artifacts; (3) a classification and annotation module for integration sites; (4) a user friendly web interface as researcher front-end to perform integration site analyses without computational skills; (5) the time speedup of all steps through parallelization (Hadoop free). CONCLUSIONS:We tested VISPA2 performances using simulated and real datasets of lentiviral vector integration sites, previously obtained from patients enrolled in a hematopoietic stem cell gene therapy clinical trial and compared the results with other preexisting tools for integration site analysis. On the computational side, VISPA2 showed a?>?6-fold speedup and improved precision and recall metrics (1 and 0.97 respectively) compared to previously developed computational pipelines. These performances indicate that VISPA2 is a fast, reliable and user-friendly tool for integration site analysis, which allows gene therapy integration data to be handled in a cost and time effective fashion. Moreover, the web access of VISPA2 ( http://openserver.itb.cnr.it/vispa/ ) ensures accessibility and ease of usage to researches of a complex analytical tool. We released the source code of VISPA2 in a public repository ( https://bitbucket.org/andreacalabria/vispa2 ).

Dataset Information

Vector Integration Sites Identification for Gene-Trap Screening in Mammalian Haploid Cells.

Publications

Vector Integration Sites Identification for Gene-Trap Screening in Mammalian Haploid Cells.

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