iRNA-seq – computational method for genome-wide assessment of acute transcriptional regulation from total RNA-seq data

RNA-seq is a sensitive and accurate technique to compare steady-state levels of RNA between different cellular states. However, as it does not provide an account of transcriptional activity per se, other technologies are needed to more precisely determine acute transcriptional responses.

Researchers from the University of Southern Denmark have developed an easy, sensitive and accurate novel computational method, IRNA-SEQ: , for genome-wide assessment of transcriptional activity based on analysis of intron coverage from total RNA-seq data. Comparison of the results derived from iRNA-seq analyses with parallel results derived using current methods for genome-wide determination of transcriptional activity, i.e. global run-on (GRO)-seq and RNA polymerase II (RNAPII) ChIP-seq, demonstrate that iRNA-seq provides similar results in terms of number of regulated genes and their fold change. However, unlike the current methods that are all very labor-intensive and demanding in terms of sample material and technologies, iRNA-seq is cheap and easy and requires very little sample material.

Outline of the iRNA-seq pipeline


(A) iRNA-seq takes SAM/BAM input files and counts reads within intron regions of the longest isoform for each gene. All regions associated with Genbank mRNAs are subtracted from the regions to be counted and the remaining intron reads are summarized for each transcript. edgeR is then used to perform differential expression analysis. (B) Screenshot from the UCSC genome browser illustrating how differential exon usage (arrow A) and incomplete annotation (arrow B) result exon reads contributing to coverage in introns of PPARG1. In the iRNA-seq pipeline, such regions are excluded using the Genbank mRNA track.

Madsen JG, Schmidt SF, Larsen BD, Loft A, Nielsen R, Mandrup S. (2016) iRNA-seq: computational method for genome-wide assessment of acute transcriptional regulation from total RNA-seq data. Nucleic Acids Res 43(6):e40. [article]

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