SMRT-Cappable-seq reveals complex operon variants in bacteria

Abstract

Current methods for genome-wide analysis of gene expression require fragmentation of original transcripts into small fragments for short-read sequencing. In bacteria, the resulting fragmented information hides operon complexity. Additionally, in vivo processing of transcripts confounds the accurate identification of the 5′ and 3′ ends of operons. Here we develop a methodology called SMRT-Cappable-seq that combines the isolation of un-fragmented primary transcripts with single-molecule long read sequencing. Applied to E. coli, this technology results in an accurate definition of the transcriptome with 34% of known operons from RegulonDB being extended by at least one gene. Furthermore, 40% of transcription termination sites have read-through that alters the gene content of the operons. As a result, most of the bacterial genes are present in multiple operon variants reminiscent of eukaryotic splicing. By providing such granularity in the operon structure, this study represents an important resource for the study of prokaryotic gene network and regulation.

Advances in bacterial transcriptome understanding: From overlapping transcription to the excludon concept

“…Contrary to this, overlapping between 3′ UTRs of contiguous genes in S. aureus was found to be more frequent than overlapping between 5′ UTRs (Lasa et al, 2011;Ruiz de Los Mozos et al, 2013). Overlapping between SigB-dependent asRNA (Yan, Boitano, Clark, & Ettwiller, 2018), named Smart-Cappable-seq, on E. coli has shown that 40% of transcription termination sites have read-through that can alter the gene content of the define operons (http://bioco mputo2.ibt.unam.mx/Opero nPred ictor /) (Taboada, Estrada, Ciria, & Merino, 2018). When the downstream genes were in the same direction, the extended transcript included at least an additional gene.…”

Explainable Transformer Models for Functional Genomics in Prokaryotes

“…First a comparison is made between the shared TSSs. In line with the criteria applied by [36], a TSSs is shared between two data sets if they are annotated within a distance of five nucleotides. The distribution of shared TSSs between the data sets is given in Figure 2a.…”

“…The creation of annotated data sets for TSSs have ushered the development of varying methodologies [8,36,14]. These methods are derived from RNA-seq, a next generation sequencing methodology.…”

“…Single Molecule, Real Time (SMRT) sequencing is used for long read sequences and has been applied in conjunction with Cappable-seq (SMRT-Cappable-seq) [36]. This technique has allowed the sequencing of full operon constructs through capping of full length transcripts.…”

Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to Listeria monocytogenes

“…With the goal to unravel globally the transcription regulatory network of a bacterium, expression profiles across many conditions can be collected without focusing on specific TFs and without genetic engineering [10,11]. Genome-wide maps of transcription start sites (TSSs) constitute another type of transcriptome data which allows to focus the search for regulatory motifs and is increasingly available for bacteria [12,13].…”