What happens if no stop codon

Brody, Ph. Featured Content. Introduction to Genomics. Polygenic Risk Scores. Normalized readthrough in D is plotted on two separate axes. Varying concentrations were tested for G 0. Six replicates separate wells were collected for each drug treatment condition in this experiment, and at least three separate experiments were performed with all compounds. Stimulation of ribosome readthrough was tested for six different AGs depicted in Figure 1—figure supplement 1 : G, gentamicin, paromomycin, neomycin, tobramycin, and amikacin.

To compare induction of ribosome readthrough by these AGs, HEKT cells were transiently transfected with the reporter, treated with AGs, and measured 24 hr later for luciferase activity. Consistent with the role of AGs as general protein synthesis inhibitors Blanchard et al.

Of the six AGs examined, G and gentamicin potently stimulated PTC readthrough in this assay, while paromomycin, neomycin, and amikacin showed lower but detectable stimulation of PTC readthrough. While reporter assays provide a powerful tool for studying readthrough of a given stop codon, the throughput of these assays is inherently limited, their output can be biased by the identify of the amino acid incorporated at a given stop codon Xue et al.

To address these limitations, we performed ribosome profiling to globally examine readthrough of NTCs in live mammalian cells. By monitoring the presence of ribosomes translating downstream of stop codons, we can identify individual readthrough events independent of protein output. Following a 24 hr treatment, cells were lysed and sequencing libraries were prepared for two biological replicates for each treatment condition.

Biological replicates were pooled for further analysis to increase read depth for these initial samples. To measure readthrough of stop codons genome-wide, we performed an average gene or metagene analysis, aligning all transcripts at their annotated stop codons and calculating normalized ribosome densities in this window. Examining translation in untreated cells Figure 2A , black-line reveals strong three-nucleotide periodicity in coding regions upstream of stop codons as expected for elongating ribosomes in the CDS.

At the stop codon itself, RPFs are enriched Figure 2A , black arrow as observed in previous studies in multiple organisms, reflecting that termination is slower than elongation Ingolia et al.

A Average gene plot showing normalized ribosome densities relative to the distance, in nucleotides, from the stop codon at position 0. Ribosome densities from untreated cells black , or cells treated for 24 hr with G orange, 0. Arrows demonstrate the height of peaks at stop codons for Untr, G, and paromomycin to facilitate comparison.

Each replicate is displayed, along with the mean value. D RRTS values are displayed for all genes in pooled replicates using box and whisker plots. Outliers are not shown. Source data from ribosome profiling analysis used in Figure 2. Two immediate differences emerge when comparing global termination in untreated cells to AG-treated cells. First, the peak of terminating ribosomes decreases in cells treated with G and paromomycin Figure 2A , orange and green arrows. The reduction in the peak of ribosomes at stop codons is consistent with increased rates of decoding of NTCs by nc-tRNAs.

We next evaluated SCR on a per transcript basis. In addition to these observed effects of aminoglycoside treatment on translation termination, we also examined effects on translation initiation and elongation.

For both of these phases of translation, G again proved the most disruptive of the AGs tested here. G treatment led to increases in ribosome occupancy at initiation codons Figure 2—figure supplement 3A while other AGs showed only modest effects on this process.

The Gdependent enrichment of initiating ribosomes was comparable between the 10 min and 24 hr time points, and was increased with a higher concentration of G To measure perturbation of translation elongation, we calculated average codon occupancies for all 61 sense codons by comparing the ribosome density at a specified codon relative to the ribosome density of the CDS Figure 2—figure supplement 3B , and averaged these measurements across all occurrences of the given codon.

AG treatment globally disrupted codon occupancies to varying extents resulting in a substantial loss-of-correlation between AG-treated and untreated cells. Of note, G treatment revealed both amino acid-specific changes wherein codon occupancies on all glycine orange and aspartic acid cyan codons were increased, as well as codon-specific changes wherein codon occupancy of a single isoleucine green codon AUA was decreased while occupancy of the other two codons AUC and AUU was unaffected.

These data reveal that aminoglycosides interfere with every phase of translation and provide additional evidence for the general inhibition of translation observed using luciferase assays Figure 1B. Ribosomes in mammalian cells protect, on average, 29—31 nucleotide fragments Ingolia et al. A useful diagnostic for validating bona fide translation in ribosome profiling data is the presence of three-nucleotide periodicity, a signature of elongating ribosomes.

By mapping ribosomal A sites of RPFs to single-nucleotide positions, we next calculated the proportions of ribosomes translating in each of the three possible reading frames. As anticipated, both untreated and Gtreated cells show strong enrichment of ribosomes translating in the frame Frame 0 of the CDS. Gtreated cells orange lines are overlaid onto untreated cells black lines. Source data from ribosome profiling analysis used in Figure 3 and Figure 4. Given the presence of these in-frame stop codons, ribosomes that read through the NTC will once again face a decision of whether to terminate translation, frameshift, or read through the downstream stop codon.

As termination remains the predominant reaction at stop codons, even when cells are treated with G, ribosome density is predicted to significantly decrease downstream of any in-frame stop codon. In contrast, when cells are treated with G, translation proceeds primarily in the same reading frame as the coding sequence.

Given that a majority of ribosomes reaching in-frame stop codons terminate translation, we next asked whether the gradual decline of ribosome density observed in Figure 3A can be explained by the fraction of transcripts that have encountered in-frame stop codons.

As distance from the NTC increases, so does the probability of encountering a termination codon Figure 3—figure supplement 2B.

Satisfyingly, this trend mirrors that of the global decline in ribosome density Figure 3A as distance from the stop codon increases. Numerous reports have demonstrated that the identity of the stop codon influences the likelihood of stop codon readthrough using reporter assays across diverse systems Schueren and Thoms, Importantly, these inserted stop codons were distributed relatively equally along the length of the mRNA and only inserted at positions not predicted to disrupt protein secondary structures Lovell et al.

Cells were transfected with these reporters and treated or not treated with G to evaluate readthrough at each stop codon. Readthrough efficiencies varied considerably between stop codon positions in a manner that did not appear to be a function of PTC proximity to the poly A tail Figure 4A with G, Figure 4—figure supplement 1A without G It is possible that the variability in SCR between the different PTCs is a consequence of different sequence contexts surrounding each stop codon.

Experiments were performed in triplicate with error bars representing one standard deviation. Two-sided Mann-Whitney U tests were performed to test for significant differences between groups of transcripts. C Read size distributions comparing lengths of reads at stop codons red to all reads black in untreated cells. D Distribution of RRTS values, in Gtreated cells, comparing the effect of the 4 nt termination codon on readthrough.

To query readthrough as a function of stop codon identity genome-wide, we again utilized the deeper ribosome profiling data sets. We sorted transcripts by stop codon identity and measured RRTS values for all transcripts in the absence and presence of G Figure 4B.

Based on structural studies revealing compaction of the mRNA in the A site of the ribosome during termination Brown et al. Indeed, as previously reported Ingolia et al. Next, we compared the effects of the twelve possible 4 nt stop codon signals on NTC readthrough Figure 4D for cells treated with G P values were adjusted using the Benjamini-Hochberg procedure Benjamini and Hochberg, and plotted using Logomaker Tareen and Kinney, for untreated top and Gtreated bottom cells Figure 5A and magnification of G data in Figure 5—figure supplement 1A.

As an alternative approach, we used a linear regression model to calculate regression coefficients for every nucleotide in the sequence window Figure 5—figure supplement 1B , a strategy that has been previously applied to readthrough of luciferase reporters Schueren et al. These distinct approaches yielded striking agreement on the identity of sequence features that yield increased SCR. A Within a sequence window corresponding to the footprint of a translating ribosome at the NTC 15 nt upstream to 12 nt downstream , the likelihood of each nucleotide increasing or decreasing RRTS is plotted with positive values indicating more readthrough and negative values indicating less readthrough.

Each nucleotide was tested using one-sided t- tests against all other nucleotides at each position for untreated top and Gtreated bottom cells. P values were adjusted using the Benjamini-Hochberg correction. Letters are scaled in proportion to the adjusted P value. B The frequencies of each nucleotide are plotted for all positions 40 nt upstream to 60 nt downstream of the stop codon.

Nucleotides are plotted in order of increasing frequencies. Source data from ribosome profiling analysis used in Figure 5. Looking broadly across this defined sequence window, several features emerge that influence SCR. As nucleotide usage in the CDS is constrained by the genetic code, we see that many patterns in this region repeat with three-nucleotide periodicity. To initially verify that G was able to at least partially restore levels of full-length TP53 protein, we analyzed TP53 protein levels by western blotting.

In untreated cells, no detectable band was observed for TP53, whereas G treatment restored full-length TP53 synthesis in a dose-dependent manner Figure 6A. We also observed production of a second, more prominent band corresponding to truncated TP Full-length protein corresponds to the expected size of the readthrough product and the truncated band corresponds to translation termination at the PTC.

Source data from ribosome profiling and RNA-seq analysis used in Figure 6. We next treated Calu-6 cells with G for 24 hr, generated lysates, and sequenced samples using ribosome profiling and RNA-seq. To verify that ribosomes were in fact reading through the PTC, we analyzed ribosome profiling reads on this message for both untreated Figure 6C and Gtreated Figure 6D cells.

For the purposes of our discussion, we will treat the RO metric as a reflection of the translational efficiency of a given mRNA. Untreated cells were compared to cells treated with G at both the 10 min and 24 hr time points Figure 7A and B. We reasoned that a 10 min treatment would capture differences in translation before activation of major transcriptional reprogramming.

Indeed, we observe induction of the unfolded protein response chaperones and foldases in the levels of both RNA-seq and RPF data at the 24 hr time point purple dots, upper right quadrant Figure 7B but not at the 10 min time point. These observations are consistent with the fact that the cell must contend with high quantities of misfolded proteins produced by miscoding events as well as C-terminal protein extensions arising from readthrough Oishi et al.

Additionally, we see translational upregulation of ATF4 at the later time point Figure 7B , orange , a critical transcription factor known to be translationally activated during stress Vattem and Wek, Several noteworthy genes are highlighted including histone genes red , selenoproteins green , chaperone proteins and foldases purple , ATF4 orange , and AMD1 blue. C-E Gene models show translation of several genes altered by G treatment orange relative to untreated black cells.

Arrows indicate the height of peaks at the stop codon for untreated black and Gtreated orange cells to facilitate comparison. The boxes depicting the start green and stop red codons and coding sequence orange of the uORF are enlarged. Source data from ribosome profiling and RNA-seq analysis used in Figure 7.

While the majority of mRNAs are neither dramatically changed in abundance nor differentially translated in response to G, there are several interesting outliers that we highlight here. First, the histone mRNAs revealed consistent changes in gene expression. A second class of genes impacted by G treatment is the selenocysteine-containing proteins.

In normal conditions, insertion of selenocysteine appears to be the rate-limiting step for translating many selenoprotein mRNAs, as this position represents the largest peak of ribosomes on these messages in untreated cells as demonstrated for two well translated selenocysteine genes Figure 7D , black lines marked by green arrow. Also, G treatment led to a reduction in the peak of ribosomes at UGA selenocysteine codons Figure 7D , orange lines and increased downstream ribosome density on these mRNAs.

It was further proposed that these accumulated ribosomes might form queues that eventually block initiation of the CDS. Upon G treatment, we see that this peak of ribosomes is strongly enriched Figure 7E , orange arrow , supporting the claim that these stalled ribosomes originate from readthrough of the NTC.

Here we used ribosome profiling to examine readthrough of stop codons genome-wide in human cell lines in untreated and aminoglycoside-treated cells. We find that aminoglycosides, and especially G, generally disrupted the normally accurate process of translation termination leading to high levels of SCR and, in turn, broad perturbation of several cellular processes.

Genome-wide levels of NTC readthrough varied considerably between different stop codons allowing investigation into sequence features driving the differences in SCR on the various stop codons. We also noted that treatment of cells with G changed the relative importance of features that impact SCR.

On the other hand, in the presence of G when miscoding by nc-tRNAs becomes more favorable, the influence of the 3 nt stop codon that is directly recognized by the nc-tRNA now better predicts SCR probability; the cellular tRNA levels may well contribute to the specificity that we observe.

Together, these observations suggest that SCR will be impacted by multiple constraints — the strength of interactions between eRF1 and the stop codon context and the likelihood of decoding a particular stop codon in that particular cellular environment.

The high levels of readthrough stimulated by G disrupted several biological processes with one of the most substantial consequences being perturbation of histone gene expression resulting in mRNA stabilization and decreased ribosome density Figure 7A and B. Due to the massive requirement for histone proteins needed during cell division, exquisite control of protein synthesis and subsequent histone mRNA decay is required as dividing cells transition through the cell cycle.

The substantial SCR resulting from G treatment results in ribosomes translating into these conserved hairpin structures Figure 7C. Interestingly, deletion of PELO in mouse epidermal stem cells increases ribosome occupancy on these messages Liakath-Ali et al. More generally, the role of ribosome rescue factors in dealing with genome-wide readthrough events remains an outstanding question.

In contrast to the histones, ribosome density was substantially increased on the selenoprotein mRNAs following G treatment. The large peaks of ribosomes normally stalled at the UGA codon sites for selenocysteine insertion were decreased in Gtreated cells; this likely reflects the fact that UGA now becomes recoded by an nc-tRNA instead of the cognate selenocysteine tRNA.

Simple replacement of selenocysteine with other amino acids has been shown to decrease function of several of these proteins Axley et al. Thus, while increased readthrough of UGA codons may generally increase the amount of full-length protein product for these mRNAs, functional levels of selenoproteins may decline with G treatment Renko et al. At the earliest time point, we see AMD1 is the most translationally upregulated mRNA in the transcriptome while at the later time point, translation still remains very high, but mRNA levels decrease substantially Figure 7A and B.

We believe that the increased RPF levels that we observe on AMD1 result from increased readthrough of the uORF stop codon that in turn allows scanning ribosomes to find the downstream start site.

Importantly, however, we see no evidence of ribosome queuing even under conditions of dramatically increased SCR that might support models of translation initiation inhibition. We wonder whether the observed reduction of AMD1 RNA levels that we observe may instead be mediated by the no-go decay pathway. Recent insights into the processes of cellular mRNA surveillance have converged on collided ribosomes as a minimal signal Ikeuchi et al.

In such a model, possibly as few as two readthrough events could trigger quality control thus providing immediate feedback to downregulate AMD1 expression.

Further experiments will be required to explore a potential role of ribosome quality control in regulating expression of AMD1. Despite the potential for interference with specific processes that we have highlighted here, nonsense-suppression therapeutics provide a promising option to target key disease-causing stop codons for selective readthrough.

Consequently, most nonsense mutations result in nonfunctional proteins. Related Concepts 9. You have authorized LearnCasting of your reading list in Scitable. Do you want to LearnCast this session?

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