Detecting actively translated open reading frames in ribosome profiling data

A Mini-review of Computational Approaches to Predict Functions and Findings of Novel Micro Peptides

:

New techniques in bioinformatics and the study of the transcriptome at a wide-scale have uncovered the fact that a large part of the genome is being translated than recently perceived thoughts and research, bringing about the creation of a various quantity of RNA with proteincoding and noncoding potential. A lot of RNA particles have been considered as noncoding due to many reasons, according to developing proofs. Like many sORFs that encode many functional micro peptides have neglected due to their tiny sizes.

:

Advanced studies reveal many major biological functions of these sORFs and their encoded micro peptides in a different and wide range of species. All the achievement in the identification of these sORFs and micro peptides is due to the progressive bioinformatics and high-throughput sequencing methods. This field has pulled in more consideration due to the detection of a large number of more sORFs and micro peptides. Nowadays, COVID-19 grabs all the attention of science as it is a sudden outbreak. sORFs of COVID-19 should be revealed for new ways to understand this virus. This review discusses ongoing progress in the systems for the identification and distinguishing proof of sORFs and micro peptides.

Maternal immune activation in mice disrupts proteostasis in the fetal brain

Maternal infection and inflammation during pregnancy are associated with neurodevelopmental disorders in offspring, but little is understood about the molecular mechanisms underlying this epidemiologic phenomenon. Here, we leveraged single-cell RNA sequencing to profile transcriptional changes in the mouse fetal brain in response to maternal immune activation (MIA) and identified perturbations in cellular pathways associated with mRNA translation, ribosome biogenesis and stress signaling. We found that MIA activates the integrated stress response (ISR) in male, but not female, MIA offspring in an interleukin-17a-dependent manner, which reduced global mRNA translation and altered nascent proteome synthesis. Moreover, blockade of ISR activation prevented the behavioral abnormalities as well as increased cortical neural activity in MIA male offspring. Our data suggest that sex-specific activation of the ISR leads to maternal inflammation-associated neurodevelopmental disorders.

LncRNA-Encoded Peptide: Functions and Predicting Methods

Long non-coding RNA (lncRNA) was originally defined as the representative of the non-coding RNAs and unable to encode. However, recent reports suggest that some lncRNAs actually contain open reading frames that encode peptides. These coding products play important roles in the pathogenesis of many diseases. Here, we summarize the regulatory pathways of mammalian lncRNA-encoded peptides in influencing muscle function, mRNA stability, gene expression, and so on. We also address the promoting and inhibiting functions of the peptides in different cancers and other diseases. Then we introduce the computational predicting methods and data resources to predict the coding ability of lncRNA. The intention of this review is to provide references for further coding research and contribute to reveal the potential prospects for targeted tumor therapy.

Alteration of Proteotranscriptomic Landscape Reveals the Transcriptional Regulatory Circuits Controlling Key-Signaling Pathways and Metabolic Reprogramming During Tumor Evolution

The proteotranscriptomic landscape depends on the transcription, mRNA-turnover, translation, and regulated-destruction of proteins. Gene-specific mRNA-to-protein correlation is the consequence of the dynamic interplays of the different regulatory processes of proteotranscriptomic landscape. So far, the critical impact of mRNA and protein stability on their subsequent correlation on a global scale remained unresolved. Whether the mRNA-to-protein correlations are constrained by their stability and conserved across mammalian species including human is unknown. Moreover, whether the stability-dependent correlation pattern is altered in the tumor has not been explored. To establish the quantitative relationship between stability and correlation between mRNA and protein levels, we performed a multi-omics data integration study across mammalian systems including diverse types of human tissues and cell lines in a genome-wide manner. The current study illuminated an important aspect of the mammalian proteotranscriptomic landscape by providing evidence that stability-constrained mRNA-to-protein correlation follows a hierarchical pattern that remains conserved across different tissues and mammalian species. By analyzing the tumor and non-tumor tissues, we further illustrated that mRNA-to-protein correlations deviate in tumor tissues. By gene-centric analysis, we harnessed the hierarchical correlation patterns to identify altered mRNA-to-protein correlation in tumors and characterized the tumor correlation-enhancing and -repressing genes. We elucidated the transcriptional regulatory circuits controlling the correlation-enhancing and -repressing genes that are associated with metabolic reprogramming and cancer-associated pathways in tumor tissue. By tightly controlling the mRNA-to-protein correlation of specific genes, the transcriptional regulatory circuits may enable the tumor cells to evolve in varying tumor microenvironment. The mRNA-to-protein correlation analysis thus can serve as a unique approach to identify the pathways prioritized by the tumor cells at different clinical stages. The component of transcriptional regulatory circuits identified by the current study can serve as potential candidates for stage-dependent anticancer therapy.

Genome-Wide Analysis of Actively Translated Open Reading Frames Using RiboTaper/ORFquant

Ribosome profiling, or Ribo-seq, provides precise information about the position of actively translating ribosomes. It can be used to identify open reading frames (ORFs) that are translated in a given sample. The RiboTaper pipeline, and the ORFquant R package, leverages the periodic distribution of such ribosomes along the ORF to perform a statistically robust test for translation which is insensitive to aperiodic noise and provides a statistically robust measure of translation. In addition to accounting for complex loci with overlapping ORFs, ORFquant is also able to use Ribo-seq as a tool for distinguishing actively translated transcripts from non-translated ones, within a given gene locus.

Codon Resolution Analysis of Ribosome Profiling Data

Translation is a central biological process in living cells. Ribosome profiling approach enables assessing translation on a global, cell-wide level. Extracting versatile information from the ribosome profiling data usually requires specialized expertise for handling the sequencing data that is not available to the broad community of experimentalists. Here, we provide an easy-to-use and modifiable workflow that uses a small set of commands and enables full data analysis in a standardized way, including precise positioning of the ribosome-protected fragments, for determining codon-specific translation features. The workflow is complemented with simple step-by-step explanations and is accessible to scientists with no computational background.

Using AnABlast for intergenic sORF prediction in the Caenorhabditis elegans genome

Motivation

Short bioactive peptides encoded by small open reading frames (sORFs) play important roles in eukaryotes. Bioinformatics prediction of ORFs is an early step in a genome sequence analysis, but sORFs encoding short peptides, often using non-AUG initiation codons, are not easily discriminated from false ORFs occurring by chance.

Results

AnABlast is a computational tool designed to highlight putative protein-coding regions in genomic DNA sequences. This protein-coding finder is independent of ORF length and reading frame shifts, thus making of AnABlast a potentially useful tool to predict sORFs. Using this algorithm, here, we report the identification of 82 putative new intergenic sORFs in the Caenorhabditis elegans genome. Sequence similarity, motif presence, expression data and RNA interference experiments support that the underlined sORFs likely encode functional peptides, encouraging the use of AnABlast as a new approach for the accurate prediction of intergenic sORFs in annotated eukaryotic genomes.

Availability and implementation

AnABlast is freely available at http://www.bioinfocabd.upo.es/ab/. The C.elegans genome browser with AnABlast results, annotated genes and all data used in this study is available at http://www.bioinfocabd.upo.es/celegans.

Supplementary information

Supplementary data are available at Bioinformatics online.

RiboDiPA: a novel tool for differential pattern analysis in Ribo-seq data

Ribosome profiling, also known as Ribo-seq, has become a popular approach to investigate regulatory mechanisms of translation in a wide variety of biological contexts. Ribo-seq not only provides a measurement of translation efficiency based on the relative abundance of ribosomes bound to transcripts, but also has the capacity to reveal dynamic and local regulation at different stages of translation based on positional information of footprints across individual transcripts. While many computational tools exist for the analysis of Ribo-seq data, no method is currently available for rigorous testing of the pattern differences in ribosome footprints. In this work, we develop a novel approach together with an R package, RiboDiPA, for Differential Pattern Analysis of Ribo-seq data. RiboDiPA allows for quick identification of genes with statistically significant differences in ribosome occupancy patterns for model organisms ranging from yeast to mammals. We show that differential pattern analysis reveals information that is distinct and complimentary to existing methods that focus on translational efficiency analysis. Using both simulated Ribo-seq footprint data and three benchmark data sets, we illustrate that RiboDiPA can uncover meaningful pattern differences across multiple biological conditions on a global scale, and pinpoint characteristic ribosome occupancy patterns at single codon resolution.

Inferring efficiency of translation initiation and elongation from ribosome profiling

One of the main goals of ribosome profiling is to quantify the rate of protein synthesis at the level of translation. Here, we develop a method for inferring translation elongation kinetics from ribosome profiling data using recent advances in mathematical modelling of mRNA translation. Our method distinguishes between the elongation rate intrinsic to the ribosome’s stepping cycle and the actual elongation rate that takes into account ribosome interference. This distinction allows us to quantify the extent of ribosomal collisions along the transcript and identify individual codons where ribosomal collisions are likely. When examining ribosome profiling in yeast, we observe that translation initiation and elongation are close to their optima and traffic is minimized at the beginning of the transcript to favour ribosome recruitment. However, we find many individual sites of congestion along the mRNAs where the probability of ribosome interference can reach \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$50\%$\end{document}. Our work provides new measures of translation initiation and elongation efficiencies, emphasizing the importance of rating these two stages of translation separately.

Readthrough of stop codons under limiting ABCE1 concentration involves frameshifting and inhibits nonsense-mediated mRNA decay

To gain insight into the mechanistic link between translation termination and nonsense-mediated mRNA decay (NMD), we depleted the ribosome recycling factor ABCE1 in human cells, resulting in an upregulation of NMD-sensitive mRNAs. Suppression of NMD on these mRNAs occurs prior to their SMG6-mediated endonucleolytic cleavage. ABCE1 depletion caused ribosome stalling at termination codons (TCs) and increased ribosome occupancy in 3′ UTRs, implying enhanced TC readthrough. ABCE1 knockdown indeed increased the rate of readthrough and continuation of translation in different reading frames, providing a possible explanation for the observed NMD inhibition, since enhanced readthrough displaces NMD activating proteins from the 3′ UTR. Our results indicate that stalling at TCs triggers ribosome collisions and activates ribosome quality control. Collectively, we show that improper translation termination can lead to readthrough of the TC, presumably due to ribosome collisions pushing the stalled ribosomes into the 3′ UTR, where it can resume translation in-frame as well as out-of-frame.

Parallel global profiling of plant TOR dynamics reveals a conserved role for LARP1 in translation

Target of rapamycin (TOR) is a protein kinase that coordinates eukaryotic metabolism. In mammals, TOR specifically promotes translation of ribosomal protein (RP) mRNAs when amino acids are available to support protein synthesis. The mechanisms controlling translation downstream from TOR remain contested, however, and are largely unexplored in plants. To define these mechanisms in plants, we globally profiled the plant TOR-regulated transcriptome, translatome, proteome, and phosphoproteome. We found that TOR regulates ribosome biogenesis in plants at multiple levels, but through mechanisms that do not directly depend on 5' oligopyrimidine tract motifs (5'TOPs) found in mammalian RP mRNAs. We then show that the TOR-LARP1-5'TOP signaling axis is conserved in plants and regulates expression of a core set of eukaryotic 5'TOP mRNAs, as well as new, plant-specific 5'TOP mRNAs. Our study illuminates ancestral roles of the TOR-LARP1-5'TOP metabolic regulatory network and provides evolutionary context for ongoing debates about the molecular function of LARP1.

Translation of noncoding RNAs and cancer

The human genome contains thousands of noncoding RNAs (ncRNAs), which are thought to lack open reading frames (ORFs) and cannot be translated. Some ncRNAs reportedly have important functions, including epigenetic regulation, chromatin remolding, protein modification, and RNA degradation, but the functions of most ncRNAs remain elusive. Through the application and development of ribosome profiling and sequencing technologies, an increasing number of studies have discovered the translation of ncRNAs. Although ncRNAs were initially defined as noncoding RNAs, a number of ncRNAs actually contain ORFs that are translated into peptides. Here, we summarize the available methods, tools, and databases for identifying and validating ncRNA-encoded peptides/proteins, and the recent findings regarding ncRNA-encoded small peptides/proteins in cancer are compiled and synthesized. Importantly, the role of ncRNA-encoding peptides/proteins has application prospects in cancer research, but some potential challenges remain unresolved. The aim of this review is to provide a theoretical basis that might promote the discovery of more peptides/proteins encoded by ncRNAs and aid the further development of novel diagnostic and prognostic cancer markers and therapeutic targets.

RiboToolkit: an integrated platform for analysis and annotation of ribosome profiling data to decode mRNA translation at codon resolution

Ribosome profiling (Ribo-seq) is a powerful technology for globally monitoring RNA translation; ranging from codon occupancy profiling, identification of actively translated open reading frames (ORFs), to the quantification of translational efficiency under various physiological or experimental conditions. However, analyzing and decoding translation information from Ribo-seq data is not trivial. Although there are many existing tools to analyze Ribo-seq data, most of these tools are designed for specific or limited functionalities and an easy-to-use integrated tool to analyze Ribo-seq data is lacking. Fortunately, the small size (26–34 nt) of ribosome protected fragments (RPFs) in Ribo-seq and the relatively small amount of sequencing data greatly facilitates the development of such a web platform, which is easy to manipulate for users with or without bioinformatic expertise. Thus, we developed RiboToolkit (http://rnabioinfor.tch.harvard.edu/RiboToolkit), a convenient, freely available, web-based service to centralize Ribo-seq data analyses, including data cleaning and quality evaluation, expression analysis based on RPFs, codon occupancy, translation efficiency analysis, differential translation analysis, functional annotation, translation metagene analysis, and identification of actively translated ORFs. Besides, easy-to-use web interfaces were developed to facilitate data analysis and intuitively visualize results. Thus, RiboToolkit will greatly facilitate the study of mRNA translation based on ribosome profiling.

Ribosome profiling reveals the effects of nitrogen application translational regulation of yield recovery after abrupt drought-flood alternation in rice

Abrupt drought-flood alternation is a frequent meteorological disaster during the summer in Southern China. The study of physiological and translation mechanisms of rice yield recovery after abrupt drought-flood alternation has great potential benefits in field production. Our results showed that yield recovery upon nitrogen (N) application after abrupt drought-flood alternation was due to the increase in effective panicle numbers per plant. The N application resulted in the regulation of physiological and biochemical as well as growth development processes, which led to a rapid growth recovery effect after abrupt drought-flood alternation stress in rice. Using ribosome profiling combined with RNA sequencing (RNA-seq) technology, the interactions between transcription and translation for N application after abrupt drought-flood alternation were analyzed. It was found that a small proportion of response genes were shared at the transcriptional and translational levels, that is, 14% of the expressed genes were upregulated and 6.6% downregulated. Further analysis revealed that the translation efficiency (TE) of the genes was influenced by their sequence characteristics, including their GC content, coding sequence length and normalized minimal free energy. Compared with the number of untranslated upstream open reading frames (uORFs), the increased number of translated uORFs promoted the improvement of TE. The TE of the uORFs for N application was lower than the control without N application after abrupt drought-flood alternation. This study characterizes the translational regulatory pattern in response to N application after abrupt drought-flood alternation stress.

FuncPEP: A Database of Functional Peptides Encoded by Non-Coding RNAs

Non-coding RNAs (ncRNAs) are essential players in many cellular processes, from normal development to oncogenic transformation. Initially, ncRNAs were defined as transcripts that lacked an open reading frame (ORF). However, multiple lines of evidence suggest that certain ncRNAs encode small peptides of less than 100 amino acids. The sequences encoding these peptides are known as small open reading frames (smORFs), many initiating with the traditional AUG start codon but terminating with atypical stop codons, suggesting a different biogenesis. The ncRNA-encoded peptides (ncPEPs) are gradually becoming appreciated as a new class of functional molecules that contribute to diverse cellular processes, and are deregulated in different diseases contributing to pathogenesis. As multiple publications have identified unique ncPEPs, we appreciated the need for assembling a new web resource that could gather information about these functional ncPEPs. We developed FuncPEP, a new database of functional ncRNA encoded peptides, containing all experimentally validated and functionally characterized ncPEPs. Currently, FuncPEP includes a comprehensive annotation of 112 functional ncPEPs and specific details regarding the ncRNA transcripts that encode these peptides. We believe that FuncPEP will serve as a platform for further deciphering the biologic significance and medical use of ncPEPs.

Ribosome profiling in plants: what is not lost in translation?

Translation is a highly dynamic cellular process whereby genetic information residing in an mRNA molecule is converted into a protein that in turn executes specific functions. However, pre-synthesized mRNA levels do not always correlate with corresponding protein levels, suggesting that translational control plays an essential role in gene regulation. A better understanding of how gene expression is regulated during translation will enable the discovery of new genes and mechanisms that control important traits in plants. Therefore, in recent years, several methods have been developed to analyse the translatome; that is, all mRNAs being actively translated at a given time, tissue, and/or developmental stage. Ribosome profiling or ribo-seq is one such technology revolutionizing our ability to analyse the translatome and in turn understand translational control of gene expression. Ribo-seq involves isolating mRNA-ribosome complexes, treating them with a RNase, and then identifying ribosome-protected mRNA regions by deep sequencing. Here, we briefly review recent ribosome profiling studies that revealed new insights into plant biology. Manipulation of novel genes identified using ribosome profiling could prove useful for increasing yield through improved biotic and abiotic stress tolerance.

Accurate detection of short and long active ORFs using Ribo-seq data

MOTIVATION

Ribo-seq, a technique for deep-sequencing ribosome-protected mRNA fragments, has enabled transcriptome-wide monitoring of translation in vivo. It has opened avenues for re-evaluating the coding potential of open reading frames (ORFs), including many short ORFs that were previously presumed to be non-translating. However, the detection of translating ORFs, specifically short ORFs, from Ribo-seq data, remains challenging due to its high heterogeneity and noise.

RESULTS

We present ribotricer, a method for detecting actively translating ORFs by directly leveraging the three-nucleotide periodicity of Ribo-seq data. Ribotricer demonstrates higher accuracy and robustness compared with other methods at detecting actively translating ORFs including short ORFs on multiple published datasets across species inclusive of Arabidopsis, Caenorhabditis elegans, Drosophila, human, mouse, rat, yeast and zebrafish.

AVAILABILITY AND IMPLEMENTATION

Ribotricer is available at https://github.com/smithlabcode/ribotricer. All analysis scripts and results are available at https://github.com/smithlabcode/ribotricer-results.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Control of translation by eukaryotic mRNA transcript leaders-Insights from high-throughput assays and computational modeling

Eukaryotic gene expression is tightly regulated during translation of mRNA to protein. Mis-regulation of translation can lead to aberrant proteins which accumulate in cancers and cause neurodegenerative diseases. Foundational studies on model genes established fundamental roles for mRNA 5' transcript leader (TL) sequences in controlling ribosome recruitment, scanning, and initiation. TL cis-regulatory elements and their corresponding trans-acting factors control cap-dependent initiation under unstressed conditions. Under stress, cap-dependent initiation is suppressed, and specific mRNA structures and sequences promote translation of stress-responsive transcripts to remodel the proteome. In this review, we summarize current knowledge of TL functions in translation initiation. We focus on insights from high-throughput analyses of ribosome occupancy, mRNA structure, RNA Binding Protein occupancy, and massively parallel reporter assays. These data-driven approaches, coupled with computational analyses and modeling, have paved the way for a comprehensive understanding of TL functions. Finally, we will discuss areas of future research on the roles of mRNA sequences and structures in translation. This article is categorized under: Translation > Translation Mechanisms RNA Evolution and Genomics > Computational Analyses of RNA RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.

uORFs: Important Cis-Regulatory Elements in Plants

Gene expression is regulated at many levels, including mRNA transcription, translation, and post-translational modification. Compared with transcriptional regulation, mRNA translational control is a more critical step in gene expression and allows for more rapid changes of encoded protein concentrations in cells. Translation is highly regulated by complex interactions between cis-acting elements and trans-acting factors. Initiation is not only the first phase of translation, but also the core of translational regulation, because it limits the rate of protein synthesis. As potent cis-regulatory elements in eukaryotic mRNAs, upstream open reading frames (uORFs) generally inhibit the translation initiation of downstream major ORFs (mORFs) through ribosome stalling. During the past few years, with the development of RNA-seq and ribosome profiling, functional uORFs have been identified and characterized in many organisms. Here, we review uORF identification, uORF classification, and uORF-mediated translation initiation. More importantly, we summarize the translational regulation of uORFs in plant metabolic pathways, morphogenesis, disease resistance, and nutrient absorption, which open up an avenue for precisely modulating the plant growth and development, as well as environmental adaption. Additionally, we also discuss prospective applications of uORFs in plant breeding.

Translation of small downstream ORFs enhances translation of canonical main open reading frames

In addition to canonical open reading frames (ORFs), thousands of translated small ORFs (containing less than 100 codons) have been identified in untranslated mRNA regions (UTRs) across eukaryotes. Small ORFs in 5′ UTRs (upstream (u)ORFs) often repress translation of the canonical ORF within the same mRNA. However, the function of translated small ORFs in the 3′ UTRs (downstream (d)ORFs) is unknown. Contrary to uORFs, we find that translation of dORFs enhances translation of their corresponding canonical ORFs. This translation stimulatory effect of dORFs depends on the number of dORFs, but not the length or peptide they encode. We propose that dORFs represent a new, strong, and universal translation regulatory mechanism in vertebrates.

A human ESC-based screen identifies a role for the translated lncRNA LINC00261 in pancreatic endocrine differentiation

Long noncoding RNAs (lncRNAs) are a heterogenous group of RNAs, which can encode small proteins. The extent to which developmentally regulated lncRNAs are translated and whether the produced microproteins are relevant for human development is unknown. Using a human embryonic stem cell (hESC)-based pancreatic differentiation system, we show that many lncRNAs in direct vicinity of lineage-determining transcription factors (TFs) are dynamically regulated, predominantly cytosolic, and highly translated. We genetically ablated ten such lncRNAs, most of them translated, and found that nine are dispensable for pancreatic endocrine cell development. However, deletion of LINC00261 diminishes insulin+ cells, in a manner independent of the nearby TF FOXA2. One-by-one disruption of each of LINC00261's open reading frames suggests that the RNA, rather than the produced microproteins, is required for endocrine development. Our work highlights extensive translation of lncRNAs during hESC pancreatic differentiation and provides a blueprint for dissection of their coding and noncoding roles.

RiboMiner: a toolset for mining multi-dimensional features of the translatome with ribosome profiling data

Background

Ribosome profiling has been widely used for studies of translation under a large variety of cellular and physiological contexts. Many of these studies have greatly benefitted from a series of data-mining tools designed for dissection of the translatome from different aspects. However, as the studies of translation advance quickly, the current toolbox still falls in short, and more specialized tools are in urgent need for deeper and more efficient mining of the important and new features of the translation landscapes.

Results

Here, we present RiboMiner, a bioinformatics toolset for mining of multi-dimensional features of the translatome with ribosome profiling data. RiboMiner performs extensive quality assessment of the data and integrates a spectrum of tools for various metagene analyses of the ribosome footprints and for detailed analyses of multiple features related to translation regulation. Visualizations of all the results are available. Many of these analyses have not been provided by previous methods. RiboMiner is highly flexible, as the pipeline could be easily adapted and customized for different scopes and targets of the studies.

Conclusions

Applications of RiboMiner on two published datasets did not only reproduced the main results reported before, but also generated novel insights into the translation regulation processes. Therefore, being complementary to the current tools, RiboMiner could be a valuable resource for dissections of the translation landscapes and the translation regulations by mining the ribosome profiling data more comprehensively and with higher resolution. RiboMiner is freely available at https://github.com/xryanglab/RiboMiner and https://pypi.org/project/RiboMiner.

mRNAs, proteins and the emerging principles of gene expression control

Gene expression involves transcription, translation and the turnover of mRNAs and proteins. The degree to which protein abundances scale with mRNA levels and the implications in cases where this dependency breaks down remain an intensely debated topic. Here we review recent mRNA-protein correlation studies in the light of the quantitative parameters of the gene expression pathway, contextual confounders and buffering mechanisms. Although protein and mRNA levels typically show reasonable correlation, we describe how transcriptomics and proteomics provide useful non-redundant readouts. Integrating both types of data can reveal exciting biology and is an essential step in refining our understanding of the principles of gene expression control.

The small peptide world in long noncoding RNAs

Long noncoding RNAs (lncRNAs) are a group of transcripts that are longer than 200 nucleotides (nt) without coding potential. Over the past decade, tens of thousands of novel lncRNAs have been annotated in animal and plant genomes because of advanced high-throughput RNA sequencing technologies and with the aid of coding transcript classifiers. Further, a considerable number of reports have revealed the existence of stable, functional small peptides (also known as micropeptides), translated from lncRNAs. In this review, we discuss the methods of lncRNA classification, the investigations regarding their coding potential and the functional significance of the peptides they encode.

Proteomic Detection and Validation of Translated Small Open Reading Frames

Small open reading frames (smORFs) encode previously unannotated polypeptides or short proteins that regulate translation in cis (eukaryotes) and/or are independently functional (prokaryotes and eukaryotes). Ongoing efforts for complete annotation and functional characterization of smORF-encoded proteins have yielded novel regulators and therapeutic targets. However, because they are excluded from protein databases, initiate at non-AUG start codons, and produce few unique tryptic peptides, unannotated small proteins cannot be detected with standard proteomic methods. Here,, we outline a procedure for mass spectrometry-based detection of translated smORFs in cultured human cells from protein extraction, digestion, and LC-MS/MS, to database preparation and data analysis. Following proteomic detection, translation from a unique smORF may be validated via siRNA-based silencing or overexpression and epitope tagging. This is necessary to unambiguously assign a peptide to a smORF within a specific transcript isoform or genomic locus. Provided that sufficient starting material is available, this workflow can be applied to any cell type/organism and adjusted to study specific (patho)physiological contexts including, but not limited to, development, stress, and disease. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: Protein extraction, size selection, and trypsin digestion Alternate Protocol 1: In-solution C8 column size selection Support Protocol 1: Chloroform/methanol precipitation Support Protocol 2: Reduction, alkylation, and in-solution protease digestion Support Protocol 3: Peptide de-salting Basic Protocol 2: Two-dimensional LC-MS/MS with ERLIC fractionation Basic Protocol 3: Transcriptomic database construction Alternate Protocol 2: Transcriptomics database generation with gffread Basic Protocol 4: Non-annotated peptide identification from LC-MS/MS data Basic Protocol 5: Validation using isotopically labeled synthetic peptide standards and siRNA Basic Protocol 6: Transcript validation using transient overexpression.

A Unified Model for the Function of YTHDF Proteins in Regulating m6A-Modified mRNA

N6-methyladenosine (m6A) is the most abundant mRNA nucleotide modification and regulates critical aspects of cellular physiology and differentiation. m6A is thought to mediate its effects through a complex network of interactions between different m6A sites and three functionally distinct cytoplasmic YTHDF m6A-binding proteins (DF1, DF2, and DF3). In contrast to the prevailing model, we show that DF proteins bind the same m6A-modified mRNAs rather than different mRNAs. Furthermore, we find that DF proteins do not induce translation in HeLa cells. Instead, the DF paralogs act redundantly to mediate mRNA degradation and cellular differentiation. The ability of DF proteins to regulate stability and differentiation becomes evident only when all three DF paralogs are depleted simultaneously. Our study reveals a unified model of m6A function in which all m6A-modified mRNAs are subjected to the combined action of YTHDF proteins in proportion to the number of m6A sites.

Deficiency of mitoribosomal S10 protein affects translation and splicing in Arabidopsis mitochondria

The ribosome is not only a protein-making machine, but also a regulatory element in protein synthesis. This view is supported by our earlier data showing that Arabidopsis mitoribosomes altered due to the silencing of the nuclear RPS10 gene encoding mitochondrial ribosomal protein S10 differentially translate mitochondrial transcripts compared with the wild-type. Here, we used ribosome profiling to determine the contribution of transcriptional and translational control in the regulation of protein synthesis in rps10 mitochondria compared with the wild-type ones. Oxidative phosphorylation system proteins are preferentially synthesized in wild-type mitochondria but this feature is lost in the mutant. The rps10 mitoribosomes show slightly reduced translation efficiency of most respiration-related proteins and at the same time markedly more efficiently synthesize ribosomal proteins and MatR and TatC proteins. The mitoribosomes deficient in S10 protein protect shorter transcript fragments which exhibit a weaker 3-nt periodicity compared with the wild-type. The decrease in the triplet periodicity is particularly drastic for genes containing introns. Notably, splicing is considerably less effective in the mutant, indicating an unexpected link between the deficiency of S10 and mitochondrial splicing. Thus, a shortage of the mitoribosomal S10 protein has wide-ranging consequences on mitochondrial gene expression.

Developmental regulation of canonical and small ORF translation from mRNAs

BACKGROUND

Ribosomal profiling has revealed the translation of thousands of sequences outside annotated protein-coding genes, including small open reading frames of less than 100 codons, and the translational regulation of many genes. Here we present an improved version of Poly-Ribo-Seq and apply it to Drosophila melanogaster embryos to extend the catalog of in vivo translated small ORFs, and to reveal the translational regulation of both small and canonical ORFs from mRNAs across embryogenesis.

RESULTS

We obtain highly correlated samples across five embryonic stages, with nearly 500 million putative ribosomal footprints mapped to mRNAs, and compare them to existing Ribo-Seq and proteomic data. Our analysis reveals, for the first time in Drosophila, footprints mapping to codons in a phased pattern, the hallmark of productive translation. We propose a simple binomial probability metric to ascertain translation probability. Our results also reveal reproducible ribosomal binding apparently not resulting in productive translation. This non-productive ribosomal binding seems to be especially prevalent amongst upstream short ORFs located in the 5' mRNA leaders, and amongst canonical ORFs during the activation of the zygotic translatome at the maternal-to zygotic transition.

CONCLUSIONS

We suggest that this non-productive ribosomal binding might be due to cis-regulatory ribosomal binding and to defective ribosomal scanning of ORFs outside periods of productive translation. Our results are compatible with the main function of upstream short ORFs being to buffer the translation of canonical canonical ORFs; and show that, in general, small ORFs in mRNAs display markers compatible with an evolutionary transitory state towards full coding function.

POSTAR2: deciphering the post-transcriptional regulatory logics

Post-transcriptional regulation of RNAs is critical to the diverse range of cellular processes. The volume of functional genomic data focusing on post-transcriptional regulation logics continues to grow in recent years. In the current database version, POSTAR2 (http://lulab.life.tsinghua.edu.cn/postar), we included the following new features and data: updated ∼500 CLIP-seq datasets (∼1200 CLIP-seq datasets in total) from six species, including human, mouse, fly, worm, Arabidopsis and yeast; added a new module ‘Translatome’, which is derived from Ribo-seq datasets and contains ∼36 million open reading frames (ORFs) in the genomes from the six species; updated and unified post-transcriptional regulation and variation data. Finally, we improved web interfaces for searching and visualizing protein–RNA interactions with multi-layer information. Meanwhile, we also merged our CLIPdb database into POSTAR2. POSTAR2 will help researchers investigate the post-transcriptional regulatory logics coordinated by RNA-binding proteins and translational landscape of cellular RNAs.

Reconsidering proteomic diversity with functional investigation of small ORFs and alternative ORFs

The discovery of functional yet non-annotated open reading frames (ORFs) throughout the genome of several species presents an unprecedented challenge in current genome annotation. These novel ORFs are shorter than annotated ones and many can be found on the same RNA, in opposition to current assumptions in annotation methodologies. Whilst the literature lacks consensus, these novel ORFs are commonly referred to as small ORFs (sORFs) or alternative ORFs (alt-ORFs). Unannotated ORFs represent an overlooked layer of complexity in the coding potential of genomes and are transforming our current vision of the nature of coding genes. In this review, we outline what constitutes a sORF or an alt-ORF and emphasize differences between both nomenclatures. We then describe complementary large-scale methods to accurately discover novel ORFs as well as yield functional insights on the novel proteins they encode. While serendipitous discoveries highlighted the functional importance of some novel ORFs, omics methods facilitate and improve their characterization to better understand physiological and pathological pathways. Functional annotation of sORFs, alt-ORFs and their corresponding microproteins will likely help fundamental and clinical research.

Computational methods for ribosome profiling data analysis

Since the introduction of the ribosome profiling technique in 2009 its popularity has greatly increased. It is widely used for the comprehensive assessment of gene expression and for studying the mechanisms of regulation at the translational level. As the number of ribosome profiling datasets being produced continues to grow, so too does the need for reliable software that can provide answers to the biological questions it can address. This review describes the computational methods and tools that have been developed to analyze ribosome profiling data at the different stages of the process. It starts with initial routine processing of raw data and follows with more specific tasks such as the identification of translated open reading frames, differential gene expression analysis, or evaluation of local or global codon decoding rates. The review pinpoints challenges associated with each step and explains the ways in which they are currently addressed. In addition it provides a comprehensive, albeit incomplete, list of publicly available software applicable to each step, which may be a beneficial starting point to those unexposed to ribosome profiling analysis. The outline of current challenges in ribosome profiling data analysis may inspire computational biologists to search for novel, potentially superior, solutions that will improve and expand the bioinformatician's toolbox for ribosome profiling data analysis. This article is characterized under: Translation > Ribosome Structure/Function RNA Evolution and Genomics > Computational Analyses of RNA Translation > Translation Mechanisms Translation > Translation Regulation.

Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes

Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides derived from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass spectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single-cell transcriptomics, ribosome profiling, and two MS/MS search tools in combination. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides, including an immunogenic peptide derived from an open reading frame downstream of the melanoma stem cell marker gene ABCB5. These findings hold great promise for the discovery of previously unknown tumor antigens for cancer immunotherapy.

Translational Landscape of Protein-Coding and Non-Protein-Coding RNAs upon Light Exposure in Arabidopsis

Light is one of the most essential environmental clues for plant growth and morphogenesis. Exposure to blue monochromatic light from darkness is a turning point for plant biological activity, and as a result dramatic changes in gene expression occur. To understand the translational impacts of blue light, we have performed ribosome profiling analysis and called translated open reading frames (ORFs) de novo within not only mRNAs but also non-coding RNAs (ncRNAs). Translation efficiency of 3,823 protein-coding ORFs, such as nuclear chloroplast-related genes, was up-regulated by blue light exposure. Moreover, the translational activation of the microRNA biogenesis-related genes, DCL1 and HYL1, was induced by blue light. Considering the 3-nucleotide codon periodicity of ribosome footprints, a few hundred short ORFs lying on ncRNAs and upstream ORFs (uORFs) on mRNAs were found that had differential translation status between blue light and dark. uORFs are known to have a negative effect on the expression of the main ORFs (mORFs) on the same mRNAs. Our analysis suggests that the translation of uORFs is likely to be more stimulated than that of the corresponding mORFs, and uORF-mediated translational repression of the mORFs in five genes was alleviated by blue light exposure. With data-based annotation of the ORFs, our analysis provides insights into the translatome in response to environmental changes, such as those involving light.

Emerging role of tumor-related functional peptides encoded by lncRNA and circRNA

Non-coding RNAs do not encode proteins and regulate various oncological processes. They are also important potential cancer diagnostic and prognostic biomarkers. Bioinformatics and translation omics have begun to elucidate the roles and modes of action of the functional peptides encoded by ncRNA. Here, recent advances in long non-coding RNA (lncRNA) and circular RNA (circRNA)-encoded small peptides are compiled and synthesized. We introduce both the computational and analytical methods used to forecast prospective ncRNAs encoding oncologically functional oligopeptides. We also present numerous specific lncRNA and circRNA-encoded proteins and their cancer-promoting or cancer-inhibiting molecular mechanisms. This information may expedite the discovery, development, and optimization of novel and efficacious cancer diagnostic, therapeutic, and prognostic protein-based tools derived from non-coding RNAs. The role of ncRNA-encoding functional peptides has promising application perspectives and potential challenges in cancer research. The aim of this review is to provide a theoretical basis and relevant references, which may promote the discovery of more functional peptides encoded by ncRNAs, and further develop novel anticancer therapeutic targets, as well as diagnostic and prognostic cancer markers.

XPRESSyourself: Enhancing, standardizing, and automating ribosome profiling computational analyses yields improved insight into data

Ribosome profiling, an application of nucleic acid sequencing for monitoring ribosome activity, has revolutionized our understanding of protein translation dynamics. This technique has been available for a decade, yet the current state and standardization of publicly available computational tools for these data is bleak. We introduce XPRESSyourself, an analytical toolkit that eliminates barriers and bottlenecks associated with this specialized data type by filling gaps in the computational toolset for both experts and non-experts of ribosome profiling. XPRESSyourself automates and standardizes analysis procedures, decreasing time-to-discovery and increasing reproducibility. This toolkit acts as a reference implementation of current best practices in ribosome profiling analysis. We demonstrate this toolkit’s performance on publicly available ribosome profiling data by rapidly identifying hypothetical mechanisms related to neurodegenerative phenotypes and neuroprotective mechanisms of the small-molecule ISRIB during acute cellular stress. XPRESSyourself brings robust, rapid analysis of ribosome-profiling data to a broad and ever-expanding audience and will lead to more reproducible and accessible measurements of translation regulation. XPRESSyourself software is perpetually open-source under the GPL-3.0 license and is hosted at https://github.com/XPRESSyourself, where users can access additional documentation and report software issues.

Stop codon context influences genome-wide stimulation of termination codon readthrough by aminoglycosides

Stop codon readthrough (SCR) occurs when the ribosome miscodes at a stop codon. Such readthrough events can be therapeutically desirable when a premature termination codon (PTC) is found in a critical gene. To study SCR in vivo in a genome-wide manner, we treated mammalian cells with aminoglycosides and performed ribosome profiling. We find that in addition to stimulating readthrough of PTCs, aminoglycosides stimulate readthrough of normal termination codons (NTCs) genome-wide. Stop codon identity, the nucleotide following the stop codon, and the surrounding mRNA sequence context all influence the likelihood of SCR. In comparison to NTCs, downstream stop codons in 3′UTRs are recognized less efficiently by ribosomes, suggesting that targeting of critical stop codons for readthrough may be achievable without general disruption of translation termination. Finally, we find that G418-induced miscoding alters gene expression with substantial effects on translation of histone genes, selenoprotein genes, and S-adenosylmethionine decarboxylase (AMD1).

Many genes provide a set of instructions needed to build a protein, which are read by structures called ribosomes through a process called translation. The genetic information contains a short, coded instruction called a stop codon which marks the end of the protein. When a ribosome finds a stop codon it should stop building and release the protein it has made.

Ribosomes do not always stop at stop codons. Certain chemicals can actually prevent ribosomes from detecting stop codons correctly, and aminoglycosides are drugs that have exactly this effect. Aminoglycosides can be used as antibiotics at low doses because they interfere with ribosomes in bacteria, but at higher doses they can also prevent ribosomes from detecting stop codons in human cells. When ribosomes do not stop at a stop codon this is called readthrough. There are different types of stop codons and some are naturally more effective at stopping ribosomes than others.

Wangen and Green have now examined the effect of an aminoglycoside called G418 on ribosomes in human cells grown in the laboratory. The results showed how ribosomes interacted with genetic information and revealed that certain stop codons are more affected by G418 than others. The stop codon and other genetic sequences around it affect the likelihood of readthrough. Wangen and Green also showed that sequences that encourage translation to stop are more common in the area around stop codons.

These findings highlight an evolutionary pressure driving more genes to develop strong stop codons that resist readthrough. Despite this, some are still more affected by drugs like G418 than others. Some genetic conditions, like cystic fibrosis, result from incorrect stop codons in genes. Drugs that promote readthrough specifically in these genes could be useful new treatments.

Inhibiting Translation Elongation with SVC112 Suppresses Cancer Stem Cells and Inhibits Growth in Head and Neck Squamous Carcinoma

Cancer stem cells (CSC) drive growth, therapy resistance, and recurrence in head and neck squamous cell carcinoma (HNSCC). Regulation of protein translation is crucial for normal stem cells and CSCs; its inhibition could disrupt stemness properties, but translation inhibitors are limited clinically due to toxicity. SVC112 is a synthetic derivative of bouvardin, a plant-derived translation elongation inhibitor. SVC112 had greater antiproliferative effects on HNSCC cells compared with the FDA-approved translation inhibitor omacetaxine mepesuccinate (HHT). SVC112 preferentially inhibited cancer cells compared with patient-matched cancer-associated fibroblasts, whereas HHT was equally toxic to both. SVC112 reduced sphere formation by cell lines and CSCs. SVC112 alone inhibited the growth of patient-derived xenografts (PDX), and SVC112 combined with radiation resulted in tumor regression in HPV-positive and HPV-negative HNSCC PDXs. Notably, CSC depletion after SVC112 correlated with tumor response. SVC112 preferentially impeded ribosomal processing of mRNAs critical for stress response and decreased CSC-related proteins including Myc and Sox2. SVC112 increased cell-cycle progression delay and slowed DNA repair following radiation, enhancing colony and sphere formation radiation effects. In summary, these data demonstrate that SVC112 suppresses CSC-related proteins, enhances the effects of radiation, and blocks growth of HNSCC PDXs by inhibiting CSCs. SIGNIFICANCE: Inhibiting protein elongation with SVC112 reduces tumor growth in head and neck squamous cell carcinoma and increases the effects of radiation by targeting the cancer stem cell pool.

Construction of High-Quality Rice Ribosome Footprint Library

High-throughput sequencing of ribosome footprints precisely maps and quantifies in vivo mRNA translation. The ribosome footprint sequencing has undergone continuing development since its original report. Here we provide a detailed protocol for construction of high-quality ribosome footprint library of rice. Rice total polysomes are isolated with a modified low ionic polysome extraction buffer. After nuclease digestion, rice ribosome footprints are extracted using SDS method followed by column purification. High-quality rice ribosome footprint library with peak reads of approximately 28-nucleotide (nt) length and strong 3-nt periodicity is constructed via key steps including rRNA depletion, end repair, 3' adapter ligation, reverse transcription, circularization, PCR enrichment and several rounds of purification. Biological significance of rice ribosome footprint library is further revealed by the comparison of transcriptomic and translatomic responses to salt stress and the utilization for novel open reading frame (ORF) identification. This improved protocol for rice ribosome footprint library construction will facilitate the global comprehension and quantitative measurement of dynamic translation in rice.

Accurate annotation of human protein-coding small open reading frames

Functional protein-coding small open reading frames (smORFs) are emerging as an important class of genes. However, the number of translated smORFs in the human genome is unclear because proteogenomic methods are not sensitive enough, and, as we show, Ribo-Seq strategies require additional measures to ensure comprehensive and accurate smORF annotation. Here, we integrate de novo transcriptome assembly and Ribo-Seq into an improved workflow that overcomes obstacles with previous methods to more confidently annotate thousands of smORFs. Evolutionary conservation analyses suggest that hundreds of smORF-encoded microproteins are likely functional. Additionally, many smORFs are regulated during fundamental biological processes, such as cell stress. Peptides derived from smORFs are also detectable on human leukocyte antigen complexes, revealing smORFs as a source of antigens. Thus, by including additional validation into our smORF annotation workflow, we accurately identify thousands of unannotated translated smORFs that will provide a rich pool of unexplored, functional human genes.

Translated Long Non-Coding Ribonucleic Acid ZFAS1 Promotes Cancer Cell Migration by Elevating Reactive Oxygen Species Production in Hepatocellular Carcinoma

Micropeptides (≤100 amino acids) are essential regulators of physiological and pathological processes, which can be encoded by small open reading frames (smORFs) derived from long non-coding RNAs (lncRNAs). Recently, lncRNA-encoded micropeptides have been shown to have essential roles in tumorigenesis. Since translated smORF identification remains technically challenging, little is known of their pathological functions in cancer. Therefore, we created classifiers to identify translated smORFs derived from lncRNAs based on ribosome-protected fragment sequencing and machine learning methods. In total, 537 putative translated smORFs were identified and the coding potential of five smORFs was experimentally validated via green fluorescent protein-tagged protein generation and mass spectrometry. After analyzing 11 lncRNA expression profiles of seven cancer types, we identified one validated translated lncRNA, ZFAS1, which was significantly up-regulated in hepatocellular carcinoma (HCC). Functional studies revealed that ZFAS1 can promote cancer cell migration by elevating intracellular reactive oxygen species production by inhibiting nicotinamide adenine dinucleotide dehydrogenase expression, indicating that translated ZFAS1 may be an essential oncogene in the progression of HCC. In this study, we systematically identified translated smORFs derived from lncRNAs and explored their potential pathological functions in cancer to improve our comprehensive understanding of the building blocks of living systems

Alternative role of noncoding RNAs: coding and noncoding properties

Noncoding RNAs (ncRNAs) have played a critical role in cellular biological functions. Recently, some peptides or proteins originating from annotated ncRNAs were identified in organism development and various diseases. Here, we briefly review several novel peptides translated by annotated ncRNAs and related key functions. In addition, we summarize the potential mechanism of bifunctional ncRNAs and propose a specific "switch" triggering the transformation from the noncoding to the coding state under certain stimuli or cellular stress. The coding properties of ncRNAs and their peptide products may provide a novel horizon in proteomic research and can be regarded as a potential therapeutic target for the treatment of various diseases.

A low-complexity region in human XRN1 directly recruits deadenylation and decapping factors in 5'-3' messenger RNA decay

XRN1 is the major cytoplasmic exoribonuclease in eukaryotes, which degrades deadenylated and decapped mRNAs in the last step of the 5'-3' mRNA decay pathway. Metazoan XRN1 interacts with decapping factors coupling the final stages of decay. Here, we reveal a direct interaction between XRN1 and the CCR4-NOT deadenylase complex mediated by a low-complexity region in XRN1, which we term the 'C-terminal interacting region' or CIR. The CIR represses reporter mRNA deadenylation in human cells when overexpressed and inhibits CCR4-NOT and isolated CAF1 deadenylase activity in vitro. Through complementation studies in an XRN1-null cell line, we dissect the specific contributions of XRN1 domains and regions toward decay of an mRNA reporter. We observe that XRN1 binding to the decapping activator EDC4 counteracts the dominant negative effect of CIR overexpression on decay. Another decapping activator PatL1 directly interacts with CIR and alleviates the CIR-mediated inhibition of CCR4-NOT activity in vitro. Ribosome profiling revealed that XRN1 loss impacts not only on mRNA levels but also on the translational efficiency of many cellular transcripts likely as a consequence of incomplete decay. Our findings reveal an additional layer of direct interactions in a tightly integrated network of factors mediating deadenylation, decapping and 5'-3' exonucleolytic decay.

Evolutionary flexibility in flooding response circuitry in angiosperms

Flooding due to extreme weather threatens crops and ecosystems. To understand variation in gene regulatory networks activated by submergence, we conducted a high-resolution analysis of chromatin accessibility and gene expression at three scales of transcript control in four angiosperms, ranging from a dryland-adapted wild species to a wetland crop. The data define a cohort of conserved submergence-activated genes with signatures of overlapping cis regulation by four transcription factor families. Syntenic genes are more highly expressed than nonsyntenic genes, yet both can have the cis motifs and chromatin accessibility associated with submergence up-regulation. Whereas the flexible circuitry spans the eudicot-monocot divide, the frequency of specific cis motifs, extent of chromatin accessibility, and degree of submergence activation are more prevalent in the wetland crop and may have adaptive importance.

uORF-Tools-Workflow for the determination of translation-regulatory upstream open reading frames

Ribosome profiling (ribo-seq) provides a means to analyze active translation by determining ribosome occupancy in a transcriptome-wide manner. The vast majority of ribosome protected fragments (RPFs) resides within the protein-coding sequence of mRNAs. However, commonly reads are also found within the transcript leader sequence (TLS) (aka 5’ untranslated region) preceding the main open reading frame (ORF), indicating the translation of regulatory upstream ORFs (uORFs). Here, we present a workflow for the identification of translation-regulatory uORFs. Specifically, uORF-Tools uses Ribo-TISH to identify uORFs within a given dataset and generates a uORF annotation file. In addition, a comprehensive human uORF annotation file, based on 35 ribo-seq files, is provided, which can serve as an alternative input file for the workflow. To assess the translation-regulatory activity of the uORFs, stimulus-induced changes in the ratio of the RPFs residing in the main ORFs relative to those found in the associated uORFs are determined. The resulting output file allows for the easy identification of candidate uORFs, which have translation-inhibitory effects on their associated main ORFs. uORF-Tools is available as a free and open Snakemake workflow at https://github.com/Biochemistry1-FFM/uORF-Tools. It is easily installed and all necessary tools are provided in a version-controlled manner, which also ensures lasting usability. uORF-Tools is designed for intuitive use and requires only limited computing times and resources.

The Plant Translatome Surveyed by Ribosome Profiling

Although transcriptome changes have long been recognized as a mechanism to induce tentative substitution of expressed genes in diverse biological processes in plants, the regulation of translation-the final step of the central dogma of molecular biology-emerged as an alternative and prominent layer in defining the output of genes. Despite these demands, the genome-wide analysis of protein synthesis has posed technical challenges, resulting in the plant translatome being poorly understood. The development of ribosome profiling promises to address the hidden aspects of translation, and its application to plants is revolutionizing our knowledge of the translatome. This review outlines the array of recent findings provided by ribosome profiling and illustrates the power of the versatile technique in green organisms.

A de novo evolved gene in the house mouse regulates female pregnancy cycles

The de novo emergence of new genes has been well documented through genomic analyses. However, a functional analysis, especially of very young protein-coding genes, is still largely lacking. Here, we identify a set of house mouse-specific protein-coding genes and assess their translation by ribosome profiling and mass spectrometry data. We functionally analyze one of them, Gm13030, which is specifically expressed in females in the oviduct. The interruption of the reading frame affects the transcriptional network in the oviducts at a specific stage of the estrous cycle. This includes the upregulation of Dcpp genes, which are known to stimulate the growth of preimplantation embryos. As a consequence, knockout females have their second litters after shorter times and have a higher infanticide rate. Given that Gm13030 shows no signs of positive selection, our findings support the hypothesis that a de novo evolved gene can directly adopt a function without much sequence adaptation.

Different species have specific genes that set them apart from other species. Yet exactly how these species-specific genes originate is not fully known. The traditional view is that existing old genes are duplicated to make a ‘spare’ copy, which can change through mutations into a new gene with a new role gradually over time. Despite there being lots of evidence supporting this theory, not all new genes found in recent years can be traced back to older genes. This led to an alternative view – that recently evolved genes can also appear ‘de novo’, and come from regions of random DNA sequences that did not previously code for a protein.

So far, the possibility of genes forming de novo during evolution has largely been supported by comparing and analyzing the genomes of related species. However, very little is known about the biological role these de novo genes play. Now, Xie et al. have generated a list of recently evolved de novo mouse genes, and carried out a detailed analysis of one de novo gene expressed in females at the time when embryos implant into the uterus wall.

To study the role of this gene, Xie et al. created a strain of knock-out mice that have a defunct version of the protein coded by the gene. Loss of this protein caused female mice to have their second litter after a shorter period of time and increased the likelihood that female mice would terminate their newborn pups. This suggests that this newly discovered de novo gene is involved in regulating the female reproductive cycles of mice.

Further analysis showed that this de novo gene counteracts the action of an older gene that promotes the implantation of embryos. This gene has therefore likely evolved due to the benefit it offers mothers, as it protects them from experiencing the increased physiological stress caused by a premature second pregnancy.

These findings support the idea that genes which have evolved de novo can have an essential biological purpose despite coming from random DNA sequences. This establishes that de novo evolution of genes is the second major mechanism of how new genes with significant biological roles can form in the genome.