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

rna-seqDetecting allelic biases from high-throughput sequencing data requires an approach that maximises sensitivity while minimizing false positives. Here, researchers from the CeMM Research Center for Molecular Medicine 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.

The researchers 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, they 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.

Availability – Allelome.PRO can be downloaded at:

Andergassen D, Dotter CP, Kulinski TM, Guenzl PM, Bammer PC, Barlow DP, Pauler FM, Hudson QJ. (2015) Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data. Nucleic Acids Res [Epub ahead of print]. [article]

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