Abstract
SummaryNascent transcript measurements derived from run-on sequencing experiments are critical for the investigation of transcriptional mechanisms and regulatory networks. However, conventional mRNA gene annotations significantly differ from the boundaries of primary transcripts. New primary transcript annotations are needed to accurately interpret run-on data. We developed the primaryTranscriptAnnotation R package to infer the transcriptional start and termination sites of primary transcripts from genomic run-on data. We then used these inferred coordinates to annotate transcriptional units identified de novo. This package provides the novel utility to integrate data-driven primary transcript annotations with transcriptional unit coordinates identified in an unbiased manner. Highlighting the importance of using accurate primary transcript coordinates, we demonstrate that this new methodology increases the detection of differentially expressed transcripts and provides more accurate quantification of RNA polymerase pause indices.Availability and implementation https://github.com/WarrenDavidAnderson/genomicsRpackage/tree/master/primaryTranscriptAnnotation.Supplementary information Supplementary data are available at Bioinformatics online.
Highlights
Quantification of nascent transcription is critical for resolving temporal patterns of gene regulation and defining gene regulatory networks
While ongoing efforts aim to increase the quality of genome annotations (Haft et al, 2018), existing gene annotations are inadequate for both quantifying nascent transcripts and determining the RNA polymerase location relative to gene features
We considered the possibility that the identification of termination sites (TTSs) could be influenced by distal enhancers or downstream promoters that are defined by bidirectional transcription (Core et al, 2014)
Summary
Quantification of nascent transcription is critical for resolving temporal patterns of gene regulation and defining gene regulatory networks. We directly infer TSSs and TTSs for annotated genes, we integrate the identified coordinates with TUs identified de novo. Our improved annotations increase the sensitivity and accuracy of detecting differential transcript expression and quantifying RNA polymerase pausing.
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