The FASTK family proteins fine-tune mitochondrial RNA processing

Transcription of the human mitochondrial genome and correct processing of the two long polycistronic transcripts are crucial for oxidative phosphorylation. According to the tRNA punctuation model, nucleolytic processing of these large precursor transcripts occurs mainly through the excision of the tRNAs that flank most rRNAs and mRNAs. However, some mRNAs are not punctuated by tRNAs, and it remains largely unknown how these non-canonical junctions are resolved. The FASTK family proteins are emerging as key players in non-canonical RNA processing. Here, we have generated human cell lines carrying single or combined knockouts of several FASTK family members to investigate their roles in non-canonical RNA processing. The most striking phenotypes were obtained with loss of FASTKD4 and FASTKD5 and with their combined double knockout. Comprehensive mitochondrial transcriptome analyses of these cell lines revealed a defect in processing at several canonical and non-canonical RNA junctions, accompanied by an increase in specific antisense transcripts. Loss of FASTKD5 led to the most severe phenotype with marked defects in mitochondrial translation of key components of the electron transport chain complexes and in oxidative phosphorylation. We reveal that the FASTK protein family members are crucial regulators of non-canonical junction and non-coding mitochondrial RNA processing.

Combined nanopore and single-molecule real-time sequencing survey of human betaherpesvirus 5 transcriptome

Long-read sequencing (LRS), a powerful novel approach, is able to read full-length transcripts and confers a major advantage over the earlier gold standard short-read sequencing in the efficiency of identifying for example polycistronic transcripts and transcript isoforms, including transcript length- and splice variants. In this work, we profile the human cytomegalovirus transcriptome using two third-generation LRS platforms: the Sequel from Pacific BioSciences, and MinION from Oxford Nanopore Technologies. We carried out both cDNA and direct RNA sequencing, and applied the LoRTIA software, developed in our laboratory, for the transcript annotations. This study identified a large number of novel transcript variants, including splice isoforms and transcript start and end site isoforms, as well as putative mRNAs with truncated in-frame ORFs (located within the larger ORFs of the canonical mRNAs), which potentially encode N-terminally truncated polypeptides. Our work also disclosed a highly complex meshwork of transcriptional read-throughs and overlaps.

Combined Nanopore and Single-Molecule Real-Time Sequencing Survey of Human Betaherpesvirus 5 Transcriptome

Long-read sequencing (LRS), a powerful novel approach, is able to read full-length transcripts and confers a major advantage over the earlier gold standard short-read sequencing in the efficiency of identifying for example polycistronic transcripts and transcript isoforms, including transcript length- and splice variants. In this work, we profile the human cytomegalovirus transcriptome using two third-generation LRS platforms: the Sequel from Pacific BioSciences, and MinION from Oxford Nanopore Technologies. We carried out both cDNA and direct RNA sequencing, and applied the LoRTIA software, developed in our laboratory, for the transcript annotations. This study identified a large number of novel transcript variants, including splice isoforms and transcript start and end site isoforms, as well as putative mRNAs with truncated in-frame ORFs (located within the larger ORFs of the canonical mRNAs), which potentially encode N-terminally truncated polypeptides. Our work also disclosed a highly complex meshwork of transcriptional read-throughs and overlaps.

Weighted Consensus Segmentations

The problem of segmenting linearly ordered data is frequently encountered in time-series analysis, computational biology, and natural language processing. Segmentations obtained independently from replicate data sets or from the same data with different methods or parameter settings pose the problem of computing an aggregate or consensus segmentation. This Segmentation Aggregation problem amounts to finding a segmentation that minimizes the sum of distances to the input segmentations. It is again a segmentation problem and can be solved by dynamic programming. The aim of this contribution is (1) to gain a better mathematical understanding of the Segmentation Aggregation problem and its solutions and (2) to demonstrate that consensus segmentations have useful applications. Extending previously known results we show that for a large class of distance functions only breakpoints present in at least one input segmentation appear in the consensus segmentation. Furthermore, we derive a bound on the size of consensus segments. As show-case applications, we investigate a yeast transcriptome and show that consensus segments provide a robust means of identifying transcriptomic units. This approach is particularly suited for dense transcriptomes with polycistronic transcripts, operons, or a lack of separation between transcripts. As a second application, we demonstrate that consensus segmentations can be used to robustly identify growth regimes from sets of replicate growth curves.

Caught between Two Genes: Accounting for Operonic Gene Structure Improves Prokaryotic RNA Sequencing Quantification

ABSTRACT RNA sequencing (RNA-seq) has matured into a reliable and low-cost assay for transcriptome profiling and has been deployed across a range of systems. The computational tool space for the analysis of RNA-seq data has kept pace with advances in sequencing. Yet tool development has largely centered around the human transcriptome. While eukaryotic and prokaryotic transcriptomes are similar, key differences in transcribed units limit the transfer of wet-lab and computational tools between the two domains. The article by M. Chung, R. S. Adkins, J. S. A. Mattick, K. R. Bradwell, et al. (mSystems 6:e00917-20, 2021, https://doi.org/10.1128/mSystems.00917-20), demonstrates that integrating prokaryote-specific strategies into existing RNA-seq analyses improves read quantification. Unlike in eukaryotes, polycistronic transcripts derived from operons lead to sequencing reads that span multiple neighboring genes. Chung et al. introduce FADU, a software tool that performs a correction for such reads and thereby improves read quantification and biological interpretation of prokaryotic RNA sequencing.

Protein dosage of the lldPRD operon is correlated with RNase E-dependent mRNA processing.

The ability of Escherichia coli to grow on L-lactate as a sole carbon source depends on the expression of the lldPRD operon. A striking feature of this operon is that the transcriptional regulator (LldR) encoding gene is located between the permease (LldP) and the dehydrogenase (LldD) encoding genes. In this study we report that dosage of the LldP, LldR, and LldD proteins is not modulated on the transcriptional level. Instead, modulation of protein dosage is primarily correlated with RNase E-dependent mRNA processing events that take place within the lldR mRNA, leading to the immediate inactivation of lldR, to differential segmental stabilities of the resulting cleavage products, and to differences in the translation efficiencies of the three cistrons. A model for the processing events controlling the molar quantities of the proteins in the lldPRD operon is presented and discussed. Importance Adjustment of gene expression is critical for proper cell function. For the case of polycistronic transcripts, posttranscriptional regulatory mechanisms can be used to fine-tune the expression of individual cistrons. Here, we elucidate how protein dosage of the Escherichia coli lldPRD operon, which presents the paradox of having the gene encoding a regulator protein located between genes that code for a permease and an enzyme, is regulated. Our results demonstrate that the key event in this regulatory mechanism involves the RNase E-dependent cleavage of the primary lldPRD transcript at internal site(s) located within the lldR cistron, resulting in a drastic decrease of intact lldR mRNA, to differential segmental stabilities of the resulting cleavage products, and to differences in the translation efficiencies of the three cistrons.

Asymmetrical effects of deafness-associated mitochondrial DNA 7516delA mutation on the processing of RNAs in the H-strand and L-strand polycistronic transcripts

In this report, we investigated the molecular mechanism underlying a deafness-associated m.7516delA mutation affecting the 5′ end processing sites of mitochondrial tRNAAsp and tRNASer(UCN). An in vitro processing experiment demonstrated that m.7516delA mutation caused the aberrant 5′ end processing of tRNASer(UCN) and tRNAAsp precursors, catalyzed by RNase P. Using cytoplasmic hybrids (cybrids) derived from one hearing-impaired Chinese family bearing the m.7516delA mutation and control, we demonstrated the asymmetrical effects of m.7516delA mutation on the processing of tRNAs in the heavy (H)-strand and light (L)-strand polycistronic transcripts. Specially, the m.7516delA mutation caused the decreased levels of tRNASer(UCN) and downstream five tRNAs, including tRNATyr from the L-strand transcripts and tRNAAsp from the H-strand transcripts. Strikingly, mutant cybrids exhibited the lower level of COX2 mRNA and accumulation of longer and uncleaved precursors of COX2 from the H-strand transcripts. Aberrant RNA metabolisms yielded variable reductions in the mitochondrial proteins, especially marked reductions in the levels of ND4, ND5, CO1, CO2 and CO3. The impairment of mitochondrial translation caused the proteostasis stress and respiratory deficiency, diminished ATP production and membrane potential, increased production of reactive oxygen species and promoted apoptosis. Our findings provide new insights into the pathophysiology of deafness arising from mitochondrial tRNA processing defects.

Eukaryotic Acquisition of a Bacterial Operon

Operons are a hallmark of bacterial genomes, where they allow concerted expression of multiple functionally related genes as single polycistronic transcripts. They are rare in eukaryotes, where each gene usually drives expression of its own independent messenger RNAs. Here we report the horizontal operon transfer of a catecholate-class siderophore biosynthesis pathway from Enterobacteriaceae into a group of closely related yeast taxa. We further show that the co-linearly arranged secondary metabolism genes are actively expressed, exhibit mainly eukaryotic transcriptional features, and enable the sequestration and uptake of iron. After transfer to the eukaryotic host, several genetic changes occurred, including the acquisition of polyadenylation sites, structural rearrangements, integration of eukaryotic genes, and secondary loss in some lineages. We conclude that the operon genes were likely captured in the shared insect gut habitat, modified for eukaryotic gene expression, and maintained by selection to adapt to the highly-competitive, iron-limited environment.

FADU: A Feature Counting Tool for Prokaryotic RNA-Seq Analysis

MotivationThe major algorithms for quantifying transcriptomics data for differential gene expression analysis were designed for analyzing data from human or human-like genomes, specifically those with single gene transcripts and distinct transcriptional boundaries that extend beyond the coding sequence (CDS) as identified through expressed sequence tags (ESTs) or EST-like sequence data. Some eukaryotic genomes and all, or nearly all, bacterial genomes require alternate methods of quantification since they lack annotation of transcriptional boundaries with EST or EST-like data, have overlapping transcriptional boundaries, and/or have polycistronic transcripts.ResultsAn algorithm was developed and tested that better quantifies transcriptomics data for differential gene expression analysis in organisms with overlapping transcriptional units and polycistronic transcripts. Using data from standard libraries originating from Escherichia coli and Ehrlichia chaffeensis, and strand-specific libraries from the Wolbachia endosymbiont wBm, FADU can derive counts for genes that are missed by HTSeq and featurecounts. Using the default parameters with the E. coli data, FADU can detect transcription of 51 more genes than HTSeq in union mode and 21 genes more than featurecounts, with 42 and 18 of these features being <300 bp, respectively. Due to its ability to derive counts for otherwise unrepresented genes without overstating their abundance, we believe FADU to be an improved tool for quantifying transcripts in prokaryotic systems for RNA-Seq analyses.Availability and implementationFADU is available at https://github.com/adkinsrs/FADU. FADU was implemented using Python3 and requires the PySAM module (version 0.12.0.1 or later)[email protected]