Dataset Information

Transposon insertion profiling by sequencing (TIPseq) for mapping LINE-1 insertions in the human genome.

ABSTRACT: Background:Transposable elements make up a significant portion of the human genome. Accurately locating these mobile DNAs is vital to understand their role as a source of structural variation and somatic mutation. To this end, laboratories have developed strategies to selectively amplify or otherwise enrich transposable element insertion sites in genomic DNA. Results:Here we describe a technique, Transposon Insertion Profiling by sequencing (TIPseq), to map Long INterspersed Element 1 (LINE-1, L1) retrotransposon insertions in the human genome. This method uses vectorette PCR to amplify species-specific L1 (L1PA1) insertion sites followed by paired-end Illumina sequencing. In addition to providing a step-by-step molecular biology protocol, we offer users a guide to our pipeline for data analysis, TIPseqHunter. Our recent studies in pancreatic and ovarian cancer demonstrate the ability of TIPseq to identify invariant (fixed), polymorphic (inherited variants), as well as somatically-acquired L1 insertions that distinguish cancer genomes from a patient's constitutional make-up. Conclusions:TIPseq provides an approach for amplifying evolutionarily young, active transposable element insertion sites from genomic DNA. Our rationale and variations on this protocol may be useful to those mapping L1 and other mobile elements in complex genomes.

SUBMITTER: Steranka JP

PROVIDER: S-EPMC6407172 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Transposon insertion profiling by sequencing (TIPseq) for mapping LINE-1 insertions in the human genome.

Steranka Jared P JP Tang Zuojian Z Grivainis Mark M Huang Cheng Ran Lisa CRL Payer Lindsay M LM Rego Fernanda O R FOR Miller Thiago Luiz Araujo TLA Galante Pedro A F PAF Ramaswami Sitharam S Heguy Adriana A Fenyö David D Boeke Jef D JD Burns Kathleen H KH

Mobile DNA 20190308

<h4>Background</h4>Transposable elements make up a significant portion of the human genome. Accurately locating these mobile DNAs is vital to understand their role as a source of structural variation and somatic mutation. To this end, laboratories have developed strategies to selectively amplify or otherwise enrich transposable element insertion sites in genomic DNA.<h4>Results</h4>Here we describe a technique, Transposon Insertion Profiling by sequencing (TIPseq), to map Long INterspersed Eleme ...[more]

PMID: 30899333

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Project description:BackgroundA critical topic of insertional mutagenesis experiments performed on model organisms is mapping the hits of artificial transposons (ATs) at nucleotide level accuracy. Mapping errors may occur when sequencing artifacts or mutations as single nucleotide polymorphisms (SNPs) and small indels are present very close to the junction between a genomic sequence and a transposon inverted repeat (TIR). Another particular item of insertional mutagenesis is mapping of the transposon self-insertions and, to our best knowledge, there is no publicly available mapping tool designed to analyze such molecular events.ResultsWe developed Genome ARTIST, a pairwise gapped aligner tool which works out both issues by means of an original, robust mapping strategy. Genome ARTIST is not designed to use next-generation sequencing (NGS) data but to analyze ATs insertions obtained in small to medium-scale mutagenesis experiments. Genome ARTIST employs a heuristic approach to find DNA sequence similarities and harnesses a multi-step implementation of a Smith-Waterman adapted algorithm to compute the mapping alignments. The experience is enhanced by easily customizable parameters and a user-friendly interface that describes the genomic landscape surrounding the insertion. Genome ARTIST is functional with many genomes of bacteria and eukaryotes available in Ensembl and GenBank repositories. Our tool specifically harnesses the sequence annotation data provided by FlyBase for Drosophila melanogaster (the fruit fly), which enables mapping of insertions relative to various genomic features such as natural transposons. Genome ARTIST was tested against other alignment tools using relevant query sequences derived from the D. melanogaster and Mus musculus (mouse) genomes. Real and simulated query sequences were also comparatively inquired, revealing that Genome ARTIST is a very robust solution for mapping transposon insertions.ConclusionsGenome ARTIST is a stand-alone user-friendly application, designed for high-accuracy mapping of transposon insertions and self-insertions. The tool is also useful for routine aligning assessments like detection of SNPs or checking the specificity of primers and probes. Genome ARTIST is an open source software and is available for download at www.genomeartist.ro and at GitHub (https://github.com/genomeartist/genomeartist ).

Project description:Transposon insertion sequencing (TIS) is a powerful high-throughput genetic technique that is transforming functional genomics in prokaryotes, because it enables genome-wide mapping of the determinants of fitness. However, current approaches for analyzing TIS data assume that selective pressures are constant over time and thus do not yield information regarding changes in the genetic requirements for growth in dynamic environments (e.g., during infection). Here, we describe structured analysis of TIS data collected as a time series, termed pattern analysis of conditional essentiality (PACE). From a temporal series of TIS data, PACE derives a quantitative assessment of each mutant's fitness over the course of an experiment and identifies mutants with related fitness profiles. In so doing, PACE circumvents major limitations of existing methodologies, specifically the need for artificial effect size thresholds and enumeration of bacterial population expansion. We used PACE to analyze TIS samples of Edwardsiella piscicida (a fish pathogen) collected over a 2-week infection period from a natural host (the flatfish turbot). PACE uncovered more genes that affect E. piscicida's fitness in vivo than were detected using a cutoff at a terminal sampling point, and it identified subpopulations of mutants with distinct fitness profiles, one of which informed the design of new live vaccine candidates. Overall, PACE enables efficient mining of time series TIS data and enhances the power and sensitivity of TIS-based analyses.IMPORTANCE Transposon insertion sequencing (TIS) enables genome-wide mapping of the genetic determinants of fitness, typically based on observations at a single sampling point. Here, we move beyond analysis of endpoint TIS data to create a framework for analysis of time series TIS data, termed pattern analysis of conditional essentiality (PACE). We applied PACE to identify genes that contribute to colonization of a natural host by the fish pathogen Edwardsiella piscicida. PACE uncovered more genes that affect E. piscicida's fitness in vivo than were detected using a terminal sampling point, and its clustering of mutants with related fitness profiles informed design of new live vaccine candidates. PACE yields insights into patterns of fitness dynamics and circumvents major limitations of existing methodologies. Finally, the PACE method should be applicable to additional "omic" time series data, including screens based on clustered regularly interspaced short palindromic repeats with Cas9 (CRISPR/Cas9).

Dataset Information

Transposon insertion profiling by sequencing (TIPseq) for mapping LINE-1 insertions in the human genome.

Publications

Transposon insertion profiling by sequencing (TIPseq) for mapping LINE-1 insertions in the human genome.

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