Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data

D. Andergassen, C. Dotter, T. Kulinski, P. Guenzl, P. Bammer, D. Barlow, F. Pauler, Q. Hudson, Nucleic Acids Research 43 (2015).

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Journal Article | Published | English

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Author
Andergassen, Daniel; Dotter, ChristophIST Austria; Kulinski, Tomasz; Guenzl, Philipp; Bammer, Philipp; Barlow, Denise; Pauler, Florian; Hudson, Quanah
Department
Abstract
Detecting allelic biases from high-throughput sequencing data requires an approach that maximises sensitivity while minimizing false positives. Here, we present Allelome.PRO, an automated user-friendly bioinformatics pipeline, which uses high-throughput sequencing data from reciprocal crosses of two genetically distinct mouse strains to detect allele-specific expression and chromatin modifications. Allelome.PRO extends approaches used in previous studies that exclusively analyzed imprinted expression to give a complete picture of the ‘allelome’ by automatically categorising the allelic expression of all genes in a given cell type into imprinted, strain-biased, biallelic or non-informative. Allelome.PRO offers increased sensitivity to analyze lowly expressed transcripts, together with a robust false discovery rate empirically calculated from variation in the sequencing data. We used RNA-seq data from mouse embryonic fibroblasts from F1 reciprocal crosses to determine a biologically relevant allelic ratio cutoff, and define for the first time an entire allelome. Furthermore, we show that Allelome.PRO detects differential enrichment of H3K4me3 over promoters from ChIP-seq data validating the RNA-seq results. This approach can be easily extended to analyze histone marks of active enhancers, or transcription factor binding sites and therefore provides a powerful tool to identify candidate cis regulatory elements genome wide.
Publishing Year
Date Published
2015-07-21
Journal Title
Nucleic Acids Research
Acknowledgement
Austrian Science Fund [FWF P25185-B22, FWF F4302- B09, FWFW1207-B09]. Funding for open access charge: Austrian Science Fund. We thank Florian Breitwieser for advice during the early stages of this project. High-throughput sequencing was conducted by the Biomedical Sequencing Facility (BSF) at CeMM in Vienna.
Volume
43
Issue
21
Article Number
e146
IST-REx-ID

Cite this

Andergassen D, Dotter C, Kulinski T, et al. Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data. Nucleic Acids Research. 2015;43(21). doi:10.1093/nar/gkv727
Andergassen, D., Dotter, C., Kulinski, T., Guenzl, P., Bammer, P., Barlow, D., … Hudson, Q. (2015). Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data. Nucleic Acids Research. Oxford University Press. https://doi.org/10.1093/nar/gkv727
Andergassen, Daniel, Christoph Dotter, Tomasz Kulinski, Philipp Guenzl, Philipp Bammer, Denise Barlow, Florian Pauler, and Quanah Hudson. “Allelome.PRO, a Pipeline to Define Allele-Specific Genomic Features from High-Throughput Sequencing Data.” Nucleic Acids Research. Oxford University Press, 2015. https://doi.org/10.1093/nar/gkv727.
D. Andergassen et al., “Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data,” Nucleic Acids Research, vol. 43, no. 21. Oxford University Press, 2015.
Andergassen D, Dotter C, Kulinski T, Guenzl P, Bammer P, Barlow D, Pauler F, Hudson Q. 2015. Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data. Nucleic Acids Research. 43(21), e146.
Andergassen, Daniel, et al. “Allelome.PRO, a Pipeline to Define Allele-Specific Genomic Features from High-Throughput Sequencing Data.” Nucleic Acids Research, vol. 43, no. 21, e146, Oxford University Press, 2015, doi:10.1093/nar/gkv727.
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