Tn-Seq Survival Profiling
Ontology highlight
ABSTRACT:
ORGANISM(S): Escherichia coli
PROVIDER: GSE147760 | GEO | 2022/10/11
REPOSITORIES: GEO
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Project description:Microarray Tracking of transposon mutants for a H. pylori mouse colonization screen described in Baldwin DN et al. 2007. Screen in NSH79 H. pylori strain background. Original 2000 clone transposon library was plated and patched to make 25 pools of 48 clones. Clones were infected into 4-8 C57Bl/6 mice and stomach bacteria from at least two mice were harvested at 1 week or one month. Semi-random PCR was used to amplify and label the DNA next to the transposon insertion from the input (Cy3) and output pool (Cy5) genomic DNA for each array. Two arrays were done per mouse. One array labeled from the left side of transposon (primers S, 2C) and one array labeled from the right side of the transposon (primers N3, 2C). Transposon insertions were defined by spots with signal four standard deviations above background in both arrays. We also counted insertions where two adjacent gene spots (after arranging the data in genome order) gave signal from the two different sides of the transposon (but not both). A pathogenicity experiment design type is where an infective agent such as a bacterium, virus, protozoan, fungus etc. infects a host organism(s) and the infective agent is assayed. Keywords: pathogenicity_design
2006-12-15 | GSE6529 | GEO
Project description:Microarray Tracking of transposon mutants for a H. pylori mouse colonization screen described in Baldwin DN et al. Screen in NSH57 H. pylori strain background. Original 50,000 clone transposon library was plated and patched to make 25 pools of 48 clones. Clones were infected into 4-8 C57Bl/6 mice and stomach bacteria from at least two mice were harvested at 1 week or one month. Semi-random PCR was used to amplify and label the DNA next to the transposon insertion from the input (Cy3) and output pool (Cy5) genomic DNA for each array. Two arrays were done per mouse. One array labeled from the left side of transposon (primers S, 2C) and one array labeled from the right side of the transposon (primers N3, 2C). Transposon insertions were defined by spots with signal four standard deviations above background in both arrays. We also counted insertions where two adjacent gene spots (after arranging the data in genome order) gave signal from the two different sides of the transposon (but not both). A pathogenicity experiment design type is where an infective agent such as a bacterium, virus, protozoan, fungus etc. infects a host organism(s) and the infective agent is assayed. Keywords: pathogenicity_design
2006-12-15 | GSE6528 | GEO
Project description:In presence of high concentrations of L-arabinose, Vibrio cholerae enters into a non-proliferative state. In V. cholerae, when L-arabinose in present into the media, it is incorporated and metabolized through the galactose pathway. In the present datasets we show that in presence of L-arabinose, transposon insertions in the galactose pathway confer a resistance to the detrimental effect of L-arabinose.
2020-11-16 | E-MTAB-9747 | biostudies-arrayexpress
Project description:Somatic transposon mutagenesis in mice is an efficient strategy to investigate the genetic mechanisms of tumorigenesis. The identification of tumor driving transposon insertions traditionally requires the generation of large tumor cohorts to obtain information about common insertion sites. Tumor driving insertions are also characterized by their clonal expansion in tumor tissue, a phenomenon that is facilitated by the slow and evolving transformation process of transposon mutagenesis. We describe here an improved approach for the detection of tumor driving insertions that assesses the clonal expansion of insertions by quantifying the relative proportion of sequence reads obtained in individual tumors. To this end, we have developed a protocol for insertion site sequencing that utilizes acoustic shearing of tumor DNA and Illumina sequencing. We analyzed various solid tumors generated by PiggyBac mutagenesis and for each tumor >10^6 reads corresponding to >10^4 insertion sites were obtained. In each tumor, 9 to 25 insertions stood out by their enriched sequence read frequencies when compared to frequencies obtained from tail DNA controls. These enriched insertions are potential clonally expanded tumor driving insertions, and thus identify candidate cancer genes. The candidate cancer genes of our study comprised many established cancer genes, but also novel candidate genes such as Mastermind-like1 (Mamld1) and Diacylglycerolkinase delta (Dgkd). We show that clonal expansion analysis by high-throughput sequencing is a robust approach for the identification of candidate cancer genes in insertional mutagenesis screens on the level of individual tumors. Solid tumors in mice were generated by somatic transposon mutagenesis with a PiggyBac transposon system. Insertion sites of transposons in 11 tumors and 6 non-cancerous tail controls were determined by Illumina high-throughput sequencing. Insertions were determined both on 5' and 3' sides of the transposon (PB5 and PB3, respectively). Quantitative analysis of read numbers revealed enrichment of certain insertions in tumors, but not in controls, and these enriched insertions identify candidate cancer genes.
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Project description:Determination of the effect of transposon insertion in Tn::Psrg mutant by RNA-seq in Pseudomonas aeruginosa IHMA87
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Project description:Somatic transposon mutagenesis in mice is an efficient strategy to investigate the genetic mechanisms of tumorigenesis. The identification of tumor driving transposon insertions traditionally requires the generation of large tumor cohorts to obtain information about common insertion sites. Tumor driving insertions are also characterized by their clonal expansion in tumor tissue, a phenomenon that is facilitated by the slow and evolving transformation process of transposon mutagenesis. We describe here an improved approach for the detection of tumor driving insertions that assesses the clonal expansion of insertions by quantifying the relative proportion of sequence reads obtained in individual tumors. To this end, we have developed a protocol for insertion site sequencing that utilizes acoustic shearing of tumor DNA and Illumina sequencing. We analyzed various solid tumors generated by PiggyBac mutagenesis and for each tumor >10^6 reads corresponding to >10^4 insertion sites were obtained. In each tumor, 9 to 25 insertions stood out by their enriched sequence read frequencies when compared to frequencies obtained from tail DNA controls. These enriched insertions are potential clonally expanded tumor driving insertions, and thus identify candidate cancer genes. The candidate cancer genes of our study comprised many established cancer genes, but also novel candidate genes such as Mastermind-like1 (Mamld1) and Diacylglycerolkinase delta (Dgkd). We show that clonal expansion analysis by high-throughput sequencing is a robust approach for the identification of candidate cancer genes in insertional mutagenesis screens on the level of individual tumors.
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Project description:Transposon insertion site sequencing (TIS) is a powerful method for associating genotype to phenotype. However, all TIS methods described to date use short nucleotide sequence reads which cannot uniquely determine the locations of transposon insertions within repeating genomic sequences where the repeat units are longer than the sequence read length. To overcome this limitation, we have developed a TIS method using Oxford Nanopore sequencing technology that generates and uses long nucleotide sequence reads; we have called this method LoRTIS (Long Read Transposon Insertion-site Sequencing). This experiment data contains sequence files generated using Nanopore and Illumina platforms. Biotin1308.fastq.gz and Biotin2508.fastq.gz are fastq files generated from nanopore technology. Rep1-Tn.fastq.gz and Rep1-Tn.fastq.gz are fastq files generated using Illumina platform. In this study, we have compared the efficiency of two methods in identification of transposon insertion sites.
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Project description:Genomic DNA from pools of H. pylori strain G27 Clones as indicated (pools of 300 (300p) or insertions in specific mapped genes) were amplifed using the MATT method to label DNA adjacent to the site of transposon insertion with the primer pairs indicated. The left side of the transposon was labeled in the Cy3 channel (Primer S) and the right side of the transposon was labeled in the Cy5 channel (Primer N). Computed
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Project description:Genomic DNA from pools of H. pylori strain G27 Clones as indicated (pools of 300 (300p) or insertions in specific mapped genes) were amplifed using the MATT method to label DNA adjacent to the site of transposon insertion with the primer pairs indicated. The left side of the transposon was labeled in the Cy3 channel (Primer S) and the right side of the transposon was labeled in the Cy5 channel (Primer N). Keywords: reference_design
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Project description:Transposon screens are powerful in vivo assays used to identify loci driving carcinogenesis. These loci are identified as Common Insertion Sites (CIS), i.e. regions with more transposon insertions than expected by chance. However, the identification of CIS is strongly affected by biases in the insertion behaviour of transposon systems. Here, we introduce Transmicron, a novel method that differs from previous methods by i) modelling neutral insertion rates based on chromatin accessibility, transcriptional activity, and sequence context, and ii) estimating oncogenic selection for each genomic region using Poisson regression to model insertion counts while controlling for neutral insertion rates. To assess the benefits of our approach, we generated a dataset applying two different transposon systems under comparable conditions. Benchmarking for enrichment of known cancer genes showed improved performance of Transmicron against state-of-the-art methods. Modelling neutral insertion rates allowed for better control of false positives and stronger agreement of the results between transposon systems. Moreover, using Poisson regression to consider intra-sample and inter-sample information proved beneficial in small and moderately-sized datasets. Transmicron is open-source and freely available. Overall, this study contributes to the understanding of transposon biology and introduces a novel approach to use this knowledge for discovering cancer driver genes.
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