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A workflow for genome-wide mapping of archaeal transcription factors with ChIP-seq.

Wilbanks EG, Larsen DJ, Neches RY, Yao AI, Wu CY, Kjolby RA, Facciotti MT - Nucleic Acids Res. (2012)

Bottom Line: Chromosomal tagging of target proteins with a compact epitope facilitates a standardized and cost-effective workflow that is compatible with high-throughput immunoprecipitation of natively expressed transcription factors.While this study focuses on the application of ChIP-seq in H. salinarum sp.NRC-1, our workflow can also be adapted for use in other archaea and bacteria with basic genetic tools.

View Article: PubMed Central - PubMed

Affiliation: University of California Davis, Department of Biomedical Engineering and Genome Center, One Shields Avenue, Davis, CA 95616, USA. egwilbanks@ucdavis.edu

ABSTRACT
Deciphering the structure of gene regulatory networks across the tree of life remains one of the major challenges in postgenomic biology. We present a novel ChIP-seq workflow for the archaea using the model organism Halobacterium salinarum sp. NRC-1 and demonstrate its application for mapping the genome-wide binding sites of natively expressed transcription factors. This end-to-end pipeline is the first protocol for ChIP-seq in archaea, with methods and tools for each stage from gene tagging to data analysis and biological discovery. Genome-wide binding sites for transcription factors with many binding sites (TfbD) are identified with sensitivity, while retaining specificity in the identification the smaller regulons (bacteriorhodopsin-activator protein). Chromosomal tagging of target proteins with a compact epitope facilitates a standardized and cost-effective workflow that is compatible with high-throughput immunoprecipitation of natively expressed transcription factors. The Pique package, an open-source bioinformatics method, is presented for identification of binding events. Relative to ChIP-Chip and qPCR, this workflow offers a robust catalog of protein-DNA binding events with improved spatial resolution and significantly decreased cost. While this study focuses on the application of ChIP-seq in H. salinarum sp. NRC-1, our workflow can also be adapted for use in other archaea and bacteria with basic genetic tools.

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Subsampling sequence coverage. Sequences were randomly sampled from a TfbD ChIPseq dataset of 6 M reads to create subsampled datasets of decreasing coverage. The number of peaks that could be identified in each subset (filled circles) is shown as a function of the number of sequence reads in the dataset. The specificity of these smaller lists is assessed as the percentage of the identified peaks which overlapped the larger 1.2 M read dataset (solid line).
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gks063-F7: Subsampling sequence coverage. Sequences were randomly sampled from a TfbD ChIPseq dataset of 6 M reads to create subsampled datasets of decreasing coverage. The number of peaks that could be identified in each subset (filled circles) is shown as a function of the number of sequence reads in the dataset. The specificity of these smaller lists is assessed as the percentage of the identified peaks which overlapped the larger 1.2 M read dataset (solid line).

Mentions: One of the main advantages to the ChIP-seq platform for small microbial genomes is the ability to decrease the experimental cost by multiplexing many samples in a single sequencing lane. We carried out an in silico analysis to determine the depth of sequencing necessary to achieve sensitive and accurate detection of binding sites. Sequence reads were randomly subsampled to decreasing coverage levels from 1.2 M reads (15.4 x coverage) to 10 000 reads (0.13 x coverage). For the TfbD dataset, the number of peaks identified remained stable down to 500K reads (5 x coverage), after which the sensitivity began to decrease (Figure 7). The specificity of binding site identification remained excellent below 500 K reads, even though the sensitivity decreased (Figure 7).Figure 7.


A workflow for genome-wide mapping of archaeal transcription factors with ChIP-seq.

Wilbanks EG, Larsen DJ, Neches RY, Yao AI, Wu CY, Kjolby RA, Facciotti MT - Nucleic Acids Res. (2012)

Subsampling sequence coverage. Sequences were randomly sampled from a TfbD ChIPseq dataset of 6 M reads to create subsampled datasets of decreasing coverage. The number of peaks that could be identified in each subset (filled circles) is shown as a function of the number of sequence reads in the dataset. The specificity of these smaller lists is assessed as the percentage of the identified peaks which overlapped the larger 1.2 M read dataset (solid line).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3378898&req=5

gks063-F7: Subsampling sequence coverage. Sequences were randomly sampled from a TfbD ChIPseq dataset of 6 M reads to create subsampled datasets of decreasing coverage. The number of peaks that could be identified in each subset (filled circles) is shown as a function of the number of sequence reads in the dataset. The specificity of these smaller lists is assessed as the percentage of the identified peaks which overlapped the larger 1.2 M read dataset (solid line).
Mentions: One of the main advantages to the ChIP-seq platform for small microbial genomes is the ability to decrease the experimental cost by multiplexing many samples in a single sequencing lane. We carried out an in silico analysis to determine the depth of sequencing necessary to achieve sensitive and accurate detection of binding sites. Sequence reads were randomly subsampled to decreasing coverage levels from 1.2 M reads (15.4 x coverage) to 10 000 reads (0.13 x coverage). For the TfbD dataset, the number of peaks identified remained stable down to 500K reads (5 x coverage), after which the sensitivity began to decrease (Figure 7). The specificity of binding site identification remained excellent below 500 K reads, even though the sensitivity decreased (Figure 7).Figure 7.

Bottom Line: Chromosomal tagging of target proteins with a compact epitope facilitates a standardized and cost-effective workflow that is compatible with high-throughput immunoprecipitation of natively expressed transcription factors.While this study focuses on the application of ChIP-seq in H. salinarum sp.NRC-1, our workflow can also be adapted for use in other archaea and bacteria with basic genetic tools.

View Article: PubMed Central - PubMed

Affiliation: University of California Davis, Department of Biomedical Engineering and Genome Center, One Shields Avenue, Davis, CA 95616, USA. egwilbanks@ucdavis.edu

ABSTRACT
Deciphering the structure of gene regulatory networks across the tree of life remains one of the major challenges in postgenomic biology. We present a novel ChIP-seq workflow for the archaea using the model organism Halobacterium salinarum sp. NRC-1 and demonstrate its application for mapping the genome-wide binding sites of natively expressed transcription factors. This end-to-end pipeline is the first protocol for ChIP-seq in archaea, with methods and tools for each stage from gene tagging to data analysis and biological discovery. Genome-wide binding sites for transcription factors with many binding sites (TfbD) are identified with sensitivity, while retaining specificity in the identification the smaller regulons (bacteriorhodopsin-activator protein). Chromosomal tagging of target proteins with a compact epitope facilitates a standardized and cost-effective workflow that is compatible with high-throughput immunoprecipitation of natively expressed transcription factors. The Pique package, an open-source bioinformatics method, is presented for identification of binding events. Relative to ChIP-Chip and qPCR, this workflow offers a robust catalog of protein-DNA binding events with improved spatial resolution and significantly decreased cost. While this study focuses on the application of ChIP-seq in H. salinarum sp. NRC-1, our workflow can also be adapted for use in other archaea and bacteria with basic genetic tools.

Show MeSH
Related in: MedlinePlus