DiffSegR: An RNA-Seq data driven method for differential expression analysis using changepoint detection

Abstract

To fully understand gene regulation, it is necessary to have a thorough understanding of both the transcriptome and the enzymatic and RNA-binding activities that shape it. While many RNA-Seq-based tools have been developed to analyze the transcriptome, most only consider the abundance of sequencing reads along annotated patterns (such as genes). These annotations are typically incomplete, leading to errors in the differential expression analysis. To address this issue, we present DiffSegR - an R package that enables the discovery of transcriptome-wide expression differences between two biological conditions using RNA-Seq data. DiffSegR does not require prior annotation and uses a multiple changepoints detection algorithm to identify the boundaries of differentially expressed regions in the per-base log2 fold change. In a few minutes of computation, DiffSegR could rightfully predict the role of chloroplast ribonuclease Mini-III in rRNA maturation and chloroplast ribonuclease PNPase in (3'/5')-degradation of rRNA, mRNA, and tRNA precursors as well as intron accumulation. We believe DiffSegR will benefit biologists working on transcriptomics as it allows access to information from a layer of the transcriptome overlooked by the classical differential expression analysis pipelines widely used today. DiffSegR is available at https://aliehrmann.github.io/DiffSegR/index.html.

An mTRAN-mRNA interaction mediates mitochondrial translation initiation in plants

“…To establish whether mTRAN1 binds the 5′ UTRs of mitochondrial mRNAs in vivo, we performed RNA immunoprecipitation sequencing (RIP-seq) on isolated mitochondria from the mTRAN1-GFP lines, using mito-GFP as a control. To discriminate the mTRAN1-specific immunoprecipitated RNA fragments from the GFP-control background, we used “DiffSegR” ( 47 , 48 ), which delineates boundaries of differential regions without using preexisting annotations, allowing precise identification of enriched regions. The RIP-seq analysis showed that mTRAN1 binds 5′ UTR regions, generally preferring the UTRs to CDS (Fig.…”