Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

PING 2.0: An R/Bioconductor package for nucleosome positioning using next-generation sequencing data

ABSTRACT: MNase-Seq and ChIP-Seq have evolved as popular techniques to study chromatin and histone modification. Although many tools have been developed to identify enriched regions, software tools for nucleosome positioning are still limited. We introduce a flexible and powerful open-source R package, PING 2.0, for nucleosome positioning using MNase-Seq data or MNase- or sonicated- ChIP-Seq data combined with either single-end or paired-end sequencing. PING uses a model-based approach, which enables nucleosome predictions even in the presence of low read counts. We illustrate PING using two paired-end datasets from Saccharomyces cerevisiae and compare its performance to nucleR and ChIPseqR. Identification of nucleosomes from two different mononucleosomes data. A yeast strain (W303 background) with the HTZ1 gene expressed a fusion with a myc epitope was used to map total and Htz1-containign nucleosome by MNase-ChIP-Seq. Cells were grown to mid-log phase and monomucleosomes were generated using MNase treatment of isolated nuclei. Especially for the sample of SC0017_61YDGAAXX_8_TCATTC, the Htz1-containing nucleosomes were enriched by immunoprecipitation using an anti-Myc antibody (3E10). DNA from both total nucleosomes and Htz1-enriched nucleosomes were purified and sequenced on an Illumina GA IIx using the by paired-end protocol.

ORGANISM(S): Saccharomyces cerevisiae

SUBMITTER: Sangsoon Woo

PROVIDER: E-GEOD-47073 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

PING 2.0: an R/Bioconductor package for nucleosome positioning using next-generation sequencing data.

Woo Sangsoon S Zhang Xuekui X Sauteraud Renan R Robert François F Gottardo Raphael R

Bioinformatics (Oxford, England) 20130620 16

<h4>Summary</h4>MNase-Seq and ChIP-Seq have evolved as popular techniques to study chromatin and histone modification. Although many tools have been developed to identify enriched regions, software tools for nucleosome positioning are still limited. We introduce a flexible and powerful open-source R package, PING 2.0, for nucleosome positioning using MNase-Seq data or MNase- or sonicated- ChIP-Seq data combined with either single-end or paired-end sequencing. PING uses a model-based approach, wh ...[more]

PMID: 23786769

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Project description:Targeted genomic enrichment followed by next-generation sequencing dramatically increased the efficiency of mutation discovery in human genomes. Here we demonstrate that these techniques also revolutionize traditional genetic approaches in model systems. We developed a two-step protocol utilizing a traditional bulk-segregant analysis (BSA) approach for positional cloning mutants in phenotype-driven forward genetic screens. First, BSA pools are 'light' sequenced for rough mapping, followed by targeted enrichment and deep-sequencing of the mutant BSA pool for the linked genomic region to fine-map and discover candidate mutations. We applied this method successfully to three Arabidopsis mutants and show that it can be scaled by multiplexing. Similarly, we applied these techniques to a gene-driven reverse genetics method (chemical driven target-selected mutagenesis or TILLING) that is used for generating gene knockouts in a wide range of organisms, including plants, invertebrates and vertebrates. We developed an efficient multiplexed genomic enrichment protocol for pre-barcoded samples. As a proof-of-principle, 770 genes were screened for induced mutations in 30 rats, which identified all but one known variants (30) as well as a large series of novel knockout and missense alleles. Mutations were retrieved at the expected frequency with a the false-positive rate of less than 1 in 6 million basepairs, which is much lower as compared to traditional mutation discovery approaches. Both methods are largely independent of the genome size due to the targeted enrichment and can thus be applied to any genetic model system of interest. Targeted genomic enrichment followed by next-generation sequencing dramatically increased the efficiency of mutation discovery in human genomes. Here we demonstrate that these techniques also revolutionize traditional genetic approaches in model systems. We developed a two-step protocol utilizing a traditional bulk-segregant analysis (BSA) approach for positional cloning mutants in phenotype-driven forward genetic screens. First, BSA pools are 'light' sequenced for rough mapping, followed by targeted enrichment and deep-sequencing of the mutant BSA pool for the linked genomic region to fine-map and discover candidate mutations. We applied this method successfully to three Arabidopsis mutants and show that it can be scaled by multiplexing. Similarly, we applied these techniques to a gene-driven reverse genetics method (chemical driven target-selected mutagenesis or TILLING) that is used for generating gene knockouts in a wide range of organisms, including plants, invertebrates and vertebrates. We developed an efficient multiplexed genomic enrichment protocol for pre-barcoded samples. As a proof-of-principle, 770 genes were screened for induced mutations in 30 rats, which identified all but one known variants (30) as well as a large series of novel knockout and missense alleles. Mutations were retrieved at the expected frequency with a the false-positive rate of less than 1 in 6 million basepairs, which is much lower as compared to traditional mutation discovery approaches. Both methods are largely independent of the genome size due to the targeted enrichment and can thus be applied to any genetic model system of interest.

Dataset Information

PING 2.0: An R/Bioconductor package for nucleosome positioning using next-generation sequencing data

Publications

PING 2.0: an R/Bioconductor package for nucleosome positioning using next-generation sequencing data.

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