The codons are written 5' to 3', as they appear in the mRNA. Figure Detail But where does translation take place within a cell? What individual substeps are a part of this process? And does translation differ between prokaryotes and eukaryotes? The answers to questions such as these reveal a great deal about the essential similarities between all species.
Within all cells, the translation machinery resides within a specialized organelle called the ribosome. In eukaryotes, mature mRNA molecules must leave the nucleus and travel to the cytoplasm , where the ribosomes are located. On the other hand, in prokaryotic organisms, ribosomes can attach to mRNA while it is still being transcribed. In all types of cells, the ribosome is composed of two subunits: the large 50S subunit and the small 30S subunit S, for svedberg unit, is a measure of sedimentation velocity and, therefore, mass.
Each subunit exists separately in the cytoplasm, but the two join together on the mRNA molecule. The tRNA molecules are adaptor molecules—they have one end that can read the triplet code in the mRNA through complementary base-pairing, and another end that attaches to a specific amino acid Chapeville et al. The idea that tRNA was an adaptor molecule was first proposed by Francis Crick, co-discoverer of DNA structure, who did much of the key work in deciphering the genetic code Crick, The rRNA catalyzes the attachment of each new amino acid to the growing chain.
Interestingly, not all regions of an mRNA molecule correspond to particular amino acids. In particular, there is an area near the 5' end of the molecule that is known as the untranslated region UTR or leader sequence. This portion of mRNA is located between the first nucleotide that is transcribed and the start codon AUG of the coding region, and it does not affect the sequence of amino acids in a protein Figure 3.
So, what is the purpose of the UTR? It turns out that the leader sequence is important because it contains a ribosome-binding site. A similar site in vertebrates was characterized by Marilyn Kozak and is thus known as the Kozak box.
If the leader is long, it may contain regulatory sequences, including binding sites for proteins, that can affect the stability of the mRNA or the efficiency of its translation. Figure 4: The translation initiation complex. When translation begins, the small subunit of the ribosome and an initiator tRNA molecule assemble on the mRNA transcript.
The small subunit of the ribosome has three binding sites: an amino acid site A , a polypeptide site P , and an exit site E. Here, the initiator tRNA molecule is shown binding after the small ribosomal subunit has assembled on the mRNA; the order in which this occurs is unique to prokaryotic cells.
In eukaryotes, the free initiator tRNA first binds the small ribosomal subunit to form a complex. Figure Detail Although methionine Met is the first amino acid incorporated into any new protein, it is not always the first amino acid in mature proteins—in many proteins, methionine is removed after translation. In fact, if a large number of proteins are sequenced and compared with their known gene sequences, methionine or formylmethionine occurs at the N-terminus of all of them.
However, not all amino acids are equally likely to occur second in the chain, and the second amino acid influences whether the initial methionine is enzymatically removed. For example, many proteins begin with methionine followed by alanine. In both prokaryotes and eukaryotes, these proteins have the methionine removed, so that alanine becomes the N-terminal amino acid Table 1. However, if the second amino acid is lysine, which is also frequently the case, methionine is not removed at least in the sample proteins that have been studied thus far.
These proteins therefore begin with methionine followed by lysine Flinta et al. Table 1 shows the N-terminal sequences of proteins in prokaryotes and eukaryotes, based on a sample of prokaryotic and eukaryotic proteins Flinta et al.
In the table, M represents methionine, A represents alanine, K represents lysine, S represents serine, and T represents threonine. Once the initiation complex is formed on the mRNA, the large ribosomal subunit binds to this complex, which causes the release of IFs initiation factors. The large subunit of the ribosome has three sites at which tRNA molecules can bind. The A amino acid site is the location at which the aminoacyl-tRNA anticodon base pairs up with the mRNA codon, ensuring that correct amino acid is added to the growing polypeptide chain.
The P polypeptide site is the location at which the amino acid is transferred from its tRNA to the growing polypeptide chain. Finally, the E exit site is the location at which the "empty" tRNA sits before being released back into the cytoplasm to bind another amino acid and repeat the process.
The ribosome is thus ready to bind the second aminoacyl-tRNA at the A site, which will be joined to the initiator methionine by the first peptide bond Figure 5. Figure 5: The large ribosomal subunit binds to the small ribosomal subunit to complete the initiation complex. They should exclude the possibility that apparent translation of pseudogenes is a result of ribosome footprints on conventional protein-coding ancestors.
In fact, this is begging the question to some extent — there may be RNAs, e. This suggests that there is substantial randomness in the methodology, which would be expected to contribute to the stochastic characteristics of the data.
From Figure 2A it appears that it is mainly the 3 nt periodicity that is driving the classification. Thus, one critical issue is to what extent such patterns can occur by chance under the multiple testing situations that are assessed. It is also unclear why we should assume that this situation cannot be the result of factors other than ribosomes or simply occur by chance when the authors states that "It is inconceivable that uniform 3nt period…".
Indeed many "peptides" are very short which would suggest a larger risk for false positive 3nt periodicity and uniform distribution of reads, especially for lowly expressed genes it is not clear if there is bias for detecting more genes with low rpf counts as truly translated. Thank you for resubmitting your work entitled "Many lncRNAs, 5'UTRs, and pseudogenes are translated and some are likely to express functional proteins" for further consideration at eLife.
Your revised article has been favorably evaluated by James Manley Senior editor , and the Reviewing editor and two reviewers of the original paper. The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below. Please note especially that the reviewers commented on the use of the words "inconceivable" and "invariable," which are not appropriate and can be misleading.
The revised manuscript addresses most of my major concerns from the original submission. In particular, it does seem that mis-mapping cannot explain potential pseudo-gene translation, and I am satisfied that the sequencing data largely reflect 80S ribosome occupancy.
This word is too strong even for the set of lncRNAs present in this sample, and more broadly, the only invariable thing in biology is the presence of surprising exceptions. Regarding the comment on "it is inconceivable the uniform 3-nt periodicity over an extended distance can result in anything other than bona fide translation".
This was mainly a concern regarding scientific style. For very few findings in science, if any, should alternative explanations be inconceivable. As discussed, 3-nt periodicity is very strong evidence for translation but as suggested by the authors it could also occur via other events and thus is not inconceivable at the single ORF level.
This may not only include biological aspects but also the stochastic nature of data which will suggest 3-nt periodicity with some false positive rate. The stochastic nature of the data was the main concern of this reviewer. The issue that I have is that there is no background model for how this relatively large proportion of the reads would stochastically result in 3nt periodicity. I did not see a false positive assessment which took into consideration what is discussed under point 1.
The false positive calculations seem to be for the classifier only Figure 2A. General comments regarding validity and the polysome experiment:. Given that the majority of sequence reads are ribosome-protected fragments of a well-defined size and correspond to codons of canonical ORFs, I cannot imagine a better definition of translation. It is far superior to polysome-associated RNA, the long-time definition, which does not even map the translated region, much less have any connection to codons.
Untranslated control RNAs are not associated with either the 80S or polysomes. The alternative explanations for the data mentioned in Review and discussed below are implausible; they are inconsistent with the very-well understood translation mechanism and the data.
In fact, the opposite is true; such complexes protect very specific regions of RNA. These are the non-ribosomal RNA-protein complexes we have analyzed them in detail in other work. As such, scanning ribosomes do not result in 3-nt periodicity; if they did, it would be hard to understand how they select initiation codons independent of reading frame.
More importantly, if one looks at ribosome profiles at classical ORFs, sequence reads start at the initiation codon. There are few if any reads upstream where the scanning ribosomes are. So, scanning ribosomes cannot possibly account for 3-nt periodicity, both in principle and according to the ribosome profiling data.
Indeed, one of the key experiments leading to the scanning ribosome model was the inability of ribosomes to bind circular RNA i. By the very definition, random binding would not occur in selected and extended regions with 3-nt periodicity.
Furthermore, we showed that the translation efficiency ribosome profiling reads: RNA seq reads of non-canonical ORFs is comparable only slightly less than conventional ORFs. The Reviewers cannot seriously dispute that classical ORFs are translated.
How then do they account for the indistinguishable 3-nt periodicity and roughly comparable translation efficiency of non-canonical ORFs? The idea that completely different mechanisms somehow yield remarkably similar results strains credulity. As mentioned above, we performed the suggested polysome association experiments and obtained the expected results. We did not perform mass spectrometry to identify peptides, because this is not validation for translation.
By analogy, transcription is measured by RNA polymerase e. The cycloheximide artifacts in that paper related to stress conditions, which are not relevant here. They also were observed in yeast, not mammalian cells. Also, the main artifact related to a broad peak downstream of the start codon, and this is not observed in our data. Moreover, we use standard Tophat parameters to eliminate non-unique reads.
I should note that we have dealt with issue in other experiments e. This is a semantic issue, which we tried to address in the Discussion. Moreover, by definition, a translated lncRNA is not really a lncRNA, since it is codes for a peptide that is synthesized although may not be stable.
Perhaps one could make some kind of distinction based on how long the peptide is with respect to RNA length, but it is unclear if this has any meaning. We are well aware of this literature, and indeed cited it and mentioned our ATF4 result as confirmation of previous knowledge. So, a non-coding RNA, by definition, is not translated. Again, the last section of the Discussion attempted to deal with the semantic issues here. Perhaps the reviewers would suggest new terminology for this situation.
More importantly, the 3-nt periodicity is striking by simple inspection, especially compared to control regions that are not translated but are bound by non-ribosomal RNA-protein complexes Figure 2C. The p-value for 3-nt periodicity null hypothesis is non-ribosomal complexes is , which is extremely compelling.
And, this p-value is generated on a 10 aa peptide for an RNA expressed at the lower limit of our analysis; longer or more highly expressed peptides would have vanishingly smaller p-values. Of course, the RibORF algorithm specifically addresses the statistical significance of 3-nt periodicity for any putative ORF; that is the whole point and major advance of the method.
Yes, 3-nt periodicity drives most, but not all, of the identification of translated ORFs. But, as discussed in point 6, the chance that the observed periodicity occurs by chance is small. If this means that there are many translated ORFs, then it is true that a very small number of ORFs may be false-positives. Indeed, we calculated the false-positive and false-negative rate in the paper, which are extremely low for any genome-scale analysis.
This attests to the power of 3-nt periodicity. The conservation analyses are straightforward though novel , and this comment is based on an incorrect premise. As indicated above, there is not a large fraction of false translation events, and all the identified translation events even those as short as 10 aa have 3-nt periodicity far above chance expectation.
The Reviewers are correct that, like all other experiments of this general type, low-expressed genes are problematic and it might be difficult to establish statistical significance. However, the Reviewers may not have realized that RibORF explicitly deals with this issue, because there it involves a probabilistic cut-off to identify translation events. As such, we never identify translation events from poorly expressed RNAs where 3-nt periodicity is hard to see due to limited sequence reads.
There is no bias for detecting more genes with low read counts; in fact, exactly the opposite, because more read counts means better statistics. Such potential exceptions do not affect our general conclusions. Of course, data for an individual ORF has a probabilistic component, which is why there are false positives and false negatives at a given threshold, but this has nothing to do with the concept.
PLoS Genet. Hastie, N. The expression of three abundance classes of messenger RNA in mouse tissues. Cell 9, — Huang, Y. Evidence against the energetic cost hypothesis for the short introns in highly expressed genes. BMC Evol. Ingolia, N.
Ribosome profiling reveals pervasive translation outside of annotated protein-coding genes. Cell Rep. Ribosome profiling of mouse embryonic stem cells reveals the complexity and dynamics of mammalian proteomes. Jeck, W. RNA 19, — Jia, H. Genome-wide computational identification and manual annotation of human long noncoding RNA genes.
RNA 16, — Kaida, D. Kapusta, A. Volatile evolution of long noncoding RNA repertoires: mechanisms and biological implications. Trends Genet. Keller, C. Cell 47, — Khalil, A. Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression. Kimura, M. Evolutionary rate at the molecular level. The Neutral Theory of Molecular Evolution.
Cambridge: Cambridge University Press. King, J. Non-Darwinian evolution. Kiss, T. Cell 70, 11— Kozak, M. A short leader sequence impairs the fidelity of initiation by eukaryotic ribosomes. Gene Expr. Lai, F. Activating RNAs associate with Mediator to enhance chromatin architecture and transcription. Li, X. Transcription factors bind thousands of active and inactive regions in the Drosophila blastoderm. Lickwar, C.
Genome-wide protein-DNA binding dynamics suggest a molecular clutch for transcription factor function. Lu, S. Analysis of the stimulatory effect of splicing on mRNA production and utilization in mammalian cells. RNA 9, — Lynch, M. The Origins of Genome Architecture. Sunderland MA: Sinauer Associates. Magny, E. Conserved regulation of cardiac calcium uptake by peptides encoded in small open reading frames.
Managadze, D. The vast, conserved mammalian lincRNome. PLoS Comput. Negative correlation between expression level and evolutionary rate of long intergenic noncoding RNAs. Martin, W. Introns and the origin of nucleus-cytosol compartmentalization.
Nature , 41— Mattick, J. The extent of functionality in the human genome. HUGO J. A global view of genomic information—moving beyond the gene and the master regulator. Memczak, S. Menet, J. Nascent-Seq reveals novel features of mouse circadian transcriptional regulation. Elife 1:e Milligan, L. Miura, P. Moazed, D. Small RNAs in transcriptional gene silencing and genome defence.
Mortazavi, A. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Methods 5, — Neil, H. Widespread bidirectional promoters are the major source of cryptic transcripts in yeast. Niu, D. Ohta, T. Slightly deleterious mutant substitutions in evolution.
Nature , 96— Palazzo, A. Acta , — The case for junk DNA. Wiley Interdiscip. RNA 4, — The signal sequence coding region promotes nuclear export of mRNA. Paris, M. Extensive divergence of transcription factor binding in Drosophila embryos with highly conserved gene expression.
Pennisi, E. Science , , Ponting, C. Evolution and functions of long noncoding RNAs. Preker, P. RNA exosome depletion reveals transcription upstream of active human promoters. Quek, X. Nucleic Acids Res. An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data. Raue, U. Association of protein biogenesis factors at the yeast ribosomal tunnel exit is affected by the translational status and nascent polypeptide sequence.
Rinn, J. RNA Function. RNA and dynamic nuclear organization. Salditt-Georgieff, M. Cell 7, — Salzman, J. Circular RNAs are the predominant transcript isoform from hundreds of human genes in diverse cell types. Sarkar, S. The genomic challenge to adaptationism. Shepard, S. The peculiarities of large intron splicing in animals.
Shibayama, Y. Transcription doi: Stark, B. Ribonuclease P: an enzyme with an essential RNA component. Stewart, A. Why transcription factor binding sites are ten nucleotides long. Struhl, K.
Tan-Wong, S. Gene loops enhance transcriptional directionality. Thiebaut, M. Transcription termination and nuclear degradation of cryptic unstable transcripts: a role for the nrd1-nab3 pathway in genome surveillance. Next, the large ribosomal subunit binds to form the complete initiation complex. During the elongation stage, the ribosome continues to translate each codon in turn. Each corresponding amino acid is added to the growing chain and linked via a bond called a peptide bond. Elongation continues until all of the codons are read.
Since there are no tRNA molecules that can recognize these codons, the ribosome recognizes that translation is complete.
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