Four methods of preparing mRNA 5' end libraries using the Illumina sequencing platform

Functional analysis of a random-sequence chromosome reveals a high level and the molecular nature of transcriptional noise in yeast cells

We measure transcriptional noise in yeast by analyzing chromatin structure and transcription of an 18-kb region of DNA whose sequence was randomly generated. Nucleosomes fully occupy random-sequence DNA, but nucleosome-depleted regions (NDRs) are much less frequent, and there are fewer well-positioned nucleosomes and shorter nucleosome arrays. Steady-state levels of random-sequence RNAs are comparable to yeast mRNAs, although transcription and decay rates are higher. Transcriptional initiation from random-sequence DNA occurs at numerous sites, indicating very low intrinsic specificity of the RNA Pol II machinery. In contrast, poly(A) profiles of random-sequence RNAs are roughly comparable to those of yeast mRNAs, suggesting limited evolutionary restraints on poly(A) site choice. Random-sequence RNAs show higher cell-to-cell variability than yeast mRNAs, suggesting that functional elements limit variability. These observations indicate that transcriptional noise occurs at high levels in yeast, and they provide insight into how chromatin and transcription patterns arise from the evolved yeast genome.

Genome-Wide Mapping of 5' Isoforms with 5'-Seq

The transcriptome is far more complex than previously assumed. Transcripts from the same gene can differ in terms of transcription start site, transcription end site, or pattern of splicing, and growing evidence supports the functional importance of these distinct transcript isoforms. Easily identifying these isoforms experimentally via library construction and high-throughput sequencing is crucial. Current library construction methods for identifying transcription start sites (5' transcript isoforms) involve large number of steps and (expensive) reagents, utilization of cDNA intermediates for adapter ligation, and are less suitable for studying low-abundance isoforms. Here, I describe a quick protocol for the generation of sequencing libraries to define capped 5' isoforms (5'-Seq) of various abundances in yeast and suggest a 5' isoform data analysis pipeline. The protocol relies on the utilization of a dephosphorylation-decapping method (oligo-capping) to generate a sequencing library from mRNA fragments and is a simplification of previously published 5' isoform protocols in terms of the handling steps, time, and cost. This method is exemplified using Saccharomyces cerevisiae mRNA, but it can be applied to various cellular conditions to study the effects of 5' transcript isoforms on transcriptional and/or translational regulation. © 2023 Wiley Periodicals LLC. Basic Protocol: Construction of a DNA sequencing library from capped 5' isoforms Support Protocol: Sequencing data analysis.

Maturation of 23S rRNA includes removal of helix H1 in many bacteria

In most bacteria, the three ribosomal RNAs (rRNAs) are encoded together in each of several near-identical operons. As soon as the nascent precursor rRNA emerges from RNA polymerase, ribosome assembly begins. This process entails ribosomal protein binding, rRNA folding, rRNA modification, and rRNA processing. In the model organisms Escherichia coli and Bacillus subtilis, rRNA processing results in similar mature rRNAs, despite substantial differences in the cohort of RNAses involved. A recent study of Flavobacterium johnsoniae, a member of the phylum Bacteroidota (formerly Bacteroidetes), revealed that helix H1 of 23S rRNA is absent from ribosomes, apparently a consequence of rRNA maturation. In this work, we mined RNA-seq data from 19 individual organisms and ocean metatranscriptomic samples to compare rRNA processing across diverse bacterial lineages. We found that mature ribosomes from multiple clades lack H1, and typically these ribosomes also lack an encoded H98. For all groups analysed, H1 is predicted to form in precursor rRNA as part of a longer leader-trailer helix. Hence, we infer that evolutionary loss of H98 sets the stage for H1 removal during 50S subunit maturation.

To cap it all off, again: dynamic capping and recapping of coding and non-coding RNAs to control transcript fate and biological activity

The addition of the methyl-7-guanosine (m⁷G) “cap” on the 5' ends of coding and some non-coding RNAs is essential for their protein coding capacity and biochemical activity, respectively. It was previously considered that capping was a constitutive process that generates a complete cap on all transcripts at steady-state. However, development of new methodologies demonstrated that steady-state capping is a dynamic and regulatable feature of many coding and non-coding RNAs. Indeed, capping status of specific RNAs can flux during differentiation and development, thereby impacting on their protein-coding capacity and activity. Moreover, in some primary cancer specimens, capping can be elevated for transcripts encoding proteins involved in proliferation and survival corresponding to their increased protein levels. Overexpression of one of the capping enzymes (RNMT), the transcription factor MYC or the eukaryotic translation initiation factor eIF4E all led to increased levels of steady-state capping of selected transcripts. Additionally, transcripts can be decapped and recapped, allowing these to be sequestered until needed. This review provides a summary of the major advances in enzymatic and affinity-based approaches to quantify m⁷G capping. Further, we summarize the evidence for regulation of capping. Capping has emerged as a significant regulatory step in RNA metabolism which is poised to impact a myriad of biological processes.

The eukaryotic translation initiation factor eIF4E elevates steady-state m7G capping of coding and noncoding transcripts

Methyl-7-guanosine (m7G) "capping" of coding and some noncoding RNAs is critical for their maturation and subsequent activity. Here, we discovered that eukaryotic translation initiation factor 4E (eIF4E), itself a cap-binding protein, drives the expression of the capping machinery and increased capping efficiency of ∼100 coding and noncoding RNAs. To quantify this, we developed enzymatic (cap quantification; CapQ) and quantitative cap immunoprecipitation (CapIP) methods. The CapQ method has the further advantage that it captures information about capping status independent of the type of 5' cap, i.e., it is not restricted to informing on m7G caps. These methodological advances led to unanticipated revelations: 1) Many RNA populations are inefficiently capped at steady state (∼30 to 50%), and eIF4E overexpression increased this to ∼60 to 100%, depending on the RNA; 2) eIF4E physically associates with noncoding RNAs in the nucleus; and 3) approximately half of eIF4E-capping targets identified are noncoding RNAs. eIF4E's association with noncoding RNAs strongly positions it to act beyond translation. Coding and noncoding capping targets have activities that influence survival, cell morphology, and cell-to-cell interaction. Given that RNA export and translation machineries typically utilize capped RNA substrates, capping regulation provides means to titrate the protein-coding capacity of the transcriptome and, for noncoding RNAs, to regulate their activities. We also discovered a cap sensitivity element (CapSE) which conferred eIF4E-dependent capping sensitivity. Finally, we observed elevated capping for specific RNAs in high-eIF4E leukemia specimens, supporting a role for cap dysregulation in malignancy. In all, levels of capping RNAs can be regulated by eIF4E.

Directional high-throughput sequencing of RNAs without gene-specific primers

Ribosomal RNA analysis is a useful tool for characterization of microbial communities. However, the lack of broad-range primers has hampered the simultaneous analysis of eukaryotic and prokaryotic members by amplicon sequencing. We present a complete workflow for directional, primer-independent sequencing of size-selected small subunit ribosomal RNA fragments. The library preparation protocol includes gel extraction of the target RNA, ligation of an RNA oligo to the 5'-end of the target, and cDNA synthesis with a tailed random-hexamer primer and further barcoding. The sequencing results of a phytoplankton mock community showed a highly similar profile to the biomass indicators. This method has universal potential for microbiome studies, and is compatible for the 5'-end sequencing of other RNA types with minimum library preparation costs.

Evolving methods for rational de novo design of functional RNA molecules

Artificial RNA molecules with novel functionality have many applications in synthetic biology, pharmacy and white biotechnology. The de novo design of such devices using computational methods and prediction tools is a resource-efficient alternative to experimental screening and selection pipelines. In this review, we describe methods common to many such computational approaches, thoroughly dissect these methods and highlight open questions for the individual steps. Initially, it is essential to investigate the biological target system, the regulatory mechanism that will be exploited, as well as the desired components in order to define design objectives. Subsequent computational design is needed to combine the selected components and to obtain novel functionality. This process can usually be split into constrained sequence sampling, the formulation of an optimization problem and an in silico analysis to narrow down the number of candidates with respect to secondary goals. Finally, experimental analysis is important to check whether the defined design objectives are indeed met in the target environment and detailed characterization experiments should be performed to improve the mechanistic models and detect missing design requirements.

A recap of RNA recapping

The N7-methylguanosine cap is a hallmark of the 5' end of eukaryotic mRNAs and is required for gene expression. Loss of the cap was believed to lead irreversibly to decay. However, nearly a decade ago, it was discovered that mammalian cells contain enzymes in the cytoplasm that are capable of restoring caps onto uncapped RNAs. In this review, we summarize recent advances in our understanding of cytoplasmic RNA recapping and discuss the biochemistry of this process and its impact on regulating and diversifying the transcriptome. Although most studies focus on mammalian RNA recapping, we also highlight new observations for recapping in disparate eukaryotic organisms, with the trypanosome recapping system appearing to be a fascinating example of convergent evolution. We conclude with emerging insights into the biological significance of RNA recapping and prospects for the future of this evolving area of study. This article is categorized under: RNA Processing > RNA Editing and Modification Translation > Translation Regulation RNA Processing > Capping and 5' End Modifications RNA Turnover and Surveillance > Regulation of RNA Stability.

Application of a Schizosaccharomyces pombe Edc1-fused Dcp1-Dcp2 decapping enzyme for transcription start site mapping

Changes in the 5' leader of an mRNA can have profound effects on its translational efficiency with little effect on abundance. Sequencing-based methods to accurately map the 5' leader by identifying the first transcribed nucleotide rely on enzymatic removal of the 5' eukaryotic cap structure by tobacco acid pyrophosphatase (TAP). However, commercial TAP production has been problematic and has now been discontinued. RppH, a bacterial enzyme that can also cleave the 5' cap, and Cap-Clip, a plant-derived enzyme, have been marketed as TAP replacements. We have engineered a Schizosaccharomyces pombe Edc1-fused Dcp1-Dcp2 decapping enzyme that functions as a superior TAP replacement. It can be purified from E. coli overexpression in high yields using standard biochemical methods. This constitutively active enzyme is four orders of magnitude more catalytically efficient than RppH at 5' cap removal, compares favorably to Cap-Clip, and the 5' monophosphorylated RNA product is suitable for standard RNA cloning methods. This engineered enzyme is a better replacement for TAP treatment than the current marketed use of RppH and can be produced cost-effectively in a general laboratory setting, unlike Cap-Clip.

Microarray-Based Gene Expression Analysis for Veterinary Pathologists: A Review

High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.

Difficulty in obtaining the complete mRNA coding sequence at 5' region (5' end mRNA artifact): Causes, consequences in biology and medicine and possible solutions for obtaining the actual amino acid sequence of proteins (Review)

The known difficulty in obtaining the actual full length, complete sequence of a messenger RNA (mRNA) may lead to the erroneous determination of its coding sequence at the 5' region (5' end mRNA artifact), and consequently to the wrong assignment of the translation start codon, leading to the inaccurate prediction of the encoded polypeptide at its amino terminus. Among the known human genes whose study was affected by this artifact, we can include disco interacting protein 2 homolog A (DIP2A; KIAA0184), Down syndrome critical region 1 (DSCR1), SON DNA binding protein (SON), trefoil factor 3 (TFF3) and URB1 ribosome biogenesis 1 homolog (URB1; KIAA0539) on chromosome 21, as well as receptor for activated C kinase 1 (RACK1, also known as GNB2L1), glutaminyl‑tRNA synthetase (QARS) and tyrosyl-DNA phosphodiesterase 2 (TDP2) along with another 474 loci, including interleukin 16 (IL16). In this review, we discuss the causes of this issue, its quantitative incidence in biomedical research, the consequences in biology and medicine, and the possible solutions for obtaining the actual amino acid sequence of proteins in the post-genomics era.

Novel mycoviruses discovered from metatranscriptomics survey of soybean phyllosphere phytobiomes

Mycoviruses can be beneficial to plants in that they can debilitate pathogenic fungi thereby reducing the severity of associated plant diseases. Studies to date have focused primarily on culturable fungi that represent a fraction of natural fungal populations. The nonculturable fungi, however, can harbor diverse populations of mycoviruses that reduce plant disease or enhance resistance to abiotic stress. Metatranscriptome analysis of field-grown plant samples using high-throughput sequencing offers the possibility of unbiased detection and quantification of mycoviruses regardless of the culturability of their fungal hosts together with the complete associated microbial consortia. In this study, we describe the fungal viromes of the phyllosphere of production soybean fields in Illinois, USA by analyzing the metatranscriptomes of thousands of soybean leaf samples collected during the 2008 and 2009 growing seasons. The analyses identified 25 partial genome sequences that represented at least 22 mycovirus genomes, only one of which had been described previously. The novel mycovirus genomes showed similarity to 10 distinct lineages including the genera Alphapartitivirus, Botybirnavirus, Endornavirus, Mitovirus, Mycoflexivirus, Ourmiavirus, Totivirus, Victorivirus, family Tombusviridae, order Mononegavirales, and the recently proposed genus Gemycircularvirus. The present study adds to the wealth of mycoviruses associated with plant phytobiomes and establishes groundwork needed for further characterization of the viruses.

The effect of heterogeneous Transcription Start Sites (TSS) on the translatome: implications for the mammalian cellular phenotype

BACKGROUND

The genetic program, as manifested as the cellular phenotype, is in large part dictated by the cell's protein composition. Since characterisation of the proteome remains technically laborious it is attractive to define the genetic expression profile using the transcriptome. However, the transcriptional landscape is complex and it is unclear as to what extent it reflects the ribosome associated mRNA population (the translatome). This is particularly pertinent for genes using multiple transcriptional start sites (TSS) generating mRNAs with heterogeneous 5' transcript leaders (5'TL). Furthermore, the relative abundance of the TSS gene variants is frequently cell-type specific. Indeed, promoter switches have been reported in pathologies such as cancer. The consequences of this 5'TL heterogeneity within the transcriptome for the translatome remain unresolved. This is not a moot point because the 5'TL plays a key role in regulating mRNA recruitment onto polysomes.

RESULTS

In this article, we have characterised both the transcriptome and translatome of the MCF7 (tumoural) and MCF10A (non-tumoural) cell lines. We identified ~550 genes exhibiting differential translation efficiency (TE). In itself, this is maybe not surprising. However, by focusing on genes exhibiting TSS heterogeneity we observed distinct differential promoter usage patterns in both the transcriptome and translatome. Only a minor fraction of these genes belonged to those exhibiting differential TE. Nonetheless, reporter assays demonstrated that the TSS variants impacted on the translational readout both quantitatively (the overall amount of protein expressed) and qualitatively (the nature of the proteins expressed).

CONCLUSIONS

The results point to considerable and distinct cell-specific 5'TL heterogeneity within both the transcriptome and translatome of the two cell lines analysed. This observation is in-line with the ribosome filter hypothesis which posits that the ribosomal machine can selectively filter information from within the transcriptome. As such it cautions against the simple extrapolation transcriptome → proteome. Furthermore, polysomal occupancy of specific gene 5'TL variants may also serve as novel disease biomarkers.