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. 2014 Sep 11;8(5):1365-79.
doi: 10.1016/j.celrep.2014.07.045. Epub 2014 Aug 21.

Ribosome profiling reveals pervasive translation outside of annotated protein-coding genes

Nicholas T Ingolia  1 , Gloria A Brar  2 , Noam Stern-Ginossar  2 , Michael S Harris  3 , Gaëlle J S Talhouarne  3 , Sarah E Jackson  4 , Mark R Wills  4 , Jonathan S Weissman  2
Affiliations

"V体育2025版" Ribosome profiling reveals pervasive translation outside of annotated protein-coding genes

Nicholas T Ingolia (V体育官网入口) et al. Cell Rep. .

Abstract

Ribosome profiling suggests that ribosomes occupy many regions of the transcriptome thought to be noncoding, including 5' UTRs and long noncoding RNAs (lncRNAs). Apparent ribosome footprints outside of protein-coding regions raise the possibility of artifacts unrelated to translation, particularly when they occupy multiple, overlapping open reading frames (ORFs). Here, we show hallmarks of translation in these footprints: copurification with the large ribosomal subunit, response to drugs targeting elongation, trinucleotide periodicity, and initiation at early AUGs. We develop a metric for distinguishing between 80S footprints and nonribosomal sources using footprint size distributions, which validates the vast majority of footprints outside of coding regions. We present evidence for polypeptide production beyond annotated genes, including the induction of immune responses following human cytomegalovirus (HCMV) infection. Translation is pervasive on cytosolic transcripts outside of conserved reading frames, and direct detection of this expanded universe of translated products enables efforts at understanding how cells manage and exploit its consequences. VSports手机版.

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Figure 1
Figure 1. Fragment length analysis distinguishes true ribosome footprints on coding and non-coding sequences
(A – E) Distribution of fragment lengths mapping to nuclear coding sequences (CDSes) compared to (A) the telomerase RNA Terc, (B) mitochondrial coding sequences, (C) snoRNA host gene Snhg5, (D) ENCODE lncRNAs, and (E) 5′ UTRs of protein-coding genes, in ribosome profiling data from emetine-treated mESCs. (F) Metric comparing the similarity of two length distributions. (G) Fragment length analysis plot of total reads per transcript and FLOSS relative to the nuclear coding sequence average. An FLOSS cutoff is based on an extreme outlier threshold for annotated coding sequences. LncRNAs resemble annotated, nuclear protein-coding genes, whereas functional RNAs and mitochondrial coding sequences are distinct. (H) As (G), comparing 5′ UTRs and coding sequences of nuclear-encoded mRNAs. (I) Read count profile on Malat1 with an inset showing ribosomes on a non-AUG uORF and the first reading frame at the 5′ end of the transcript. An inset shows the fragment length distribution for the first reading frame, which matches the overall coding sequence average, and the whole transcript, which does not. (J) Fragment length analysis showing the shift from the entire Malat1 transcript, which contains substantial background, to the first Malat1 reading frame, which contains true ribosome footprints. (K) Read count profile acros the primary Gas5 transcript with the snoRNAs and the fully-spliced transcript shown. (L) As (J) for the primary Gas5 transcript, containing snoRNA precursors, and the fully spliced product.
Figure 2
Figure 2. Elongation inhibitors shift ribosome footprint sizes
(A) Cumulative length distribution shows ~1 nt larger footprints on annotated coding sequences from emetine-versus cycloheximide-treated cells (Ingolia et al., 2011). (B) LncRNA and (C) 5′ UTR footprints from transcripts passing the FLOSS cutoff show a similar length shift, whereas background from (D) classical non-coding RNAs do not. (E) Experimental design with e cycloheximide-treated yeast polysomes as an internal standard for nuclease digestion and library generation. (F) Annotated coding seuqences and (G) lncRNAs again show larger footprints in emetine-treated cells. (H) Cycloheximide-stabilizied footprints are not larger in the emetine-treated mESC lysate sample.
Figure 3
Figure 3. Ribosome affinity purification separates 80S footprints from background RNA
(A) Schematic showing that affinity purification of tagged 60S ribosome subunits recovers 80S footprints but depletes background from non-ribosomal RNPs, potential scanning 40S footprints, and footprints of untagged yeast 80S ribosomes are also depleted. (B) Human ribosome footprints are retained during ribosome affinity purification while yeast ribosome footprints (excepting the yeast biotin carrier ACC1) are depleted. (C) Fragment length analysis of nuclear and mitochondrial coding sequences and of functional non-coding RNAs in HEK cells. A fragment length score cutoff based on extreme outliers relative to coding sequences excludes background fragments. (D) Ribosome footprints are retained during ribosome affinity purification while mitochondrial footprints and non-coding RNAs are depleted. (E, F) Ribosome footprints on 5′ UTRs are retained during affinity purification of the 60S ribosomal subunit. (G) Fragment length analysis of ENCODE lncRNAs, identifying a small number of transcripts with likely non-ribosomal contamination. (H, I) Ribosome footprints on lncRNAs are retained during ribosome affinity purification, whereas many sources of non-ribosomal contamination, including the nuclear non-coding RNA XIST, are depleted.
Figure 4
Figure 4. Ribosomes translate detectable reading frames on lncRNAs
(A) Schematic of AUG start site detection using two harringtonine samples (from 120 s and 150 s treatment). The start site is an AUG codon with a peak in footprint density – higher occupancy than flanking codons – selected as the highest occupancy among peaks at AUGs. (B) AUG start sites typically show the highest footprint density among all codons, not just all AUGs with peaks. (C) AUG start sites typically fall in the first few hundred nt of transcripts, and (inset) near the beginning of the transcript. (D) AUG start sites are typically among the first AUG codons on transcripts, with relative positions shown in the histogram and absolute index shown in the pie chart (i.e., nearly half of AUG start sites are the first AUG on the transcript overall). (E) Overall ribosome occupancy is higher in the ORFs downstream of AUG start sites, relative to the overall density on the transcript. (F) Footprints on As downstream of detected AUG start sites and upstream of the stop codon are biased towards the frame of the ORF. Annotated protein-coding genes show similar reading frame bias within the ORF but not in the 5′ UTR (upstream) or 3′ UTR (downstream).
Figure 5
Figure 5. Novel meiotic reading frames based on true ribosome footprints yield protein products
(A – D) Distribution of fragment lengths mapping to nuclear coding sequences compared to (A) classical non-coding RNAs, meiotic lncRNAs, and mitochondrial transcripts, (B) novel independent ORFs, (C) translated AUG uORFs, and (D) translated non-AUG uORFs. (E, F) Fragment length analysis of yeast coding sequences compared to (E) classical non-coding RNAs and (F) novel independent ORFs and AUG uORFs. (G, H) Ribosome profiling and mRNA-Seq data for novel reading frames showing meiotic induction (G) or repression (H) of a ~75 codon ORF on an independent transcript (Brar et al., 2012). (I) Western blot confirming meiotic expression of the Unit14431-GFP fusion. (J) Microscopy on meiotic yeast reveals mitochondrial targeting of the Unit14431-GFP fusion. (K) Western blot confirming vegetative expression of the Unit7541-GFP fusion. (L) Microscopy demonstrating nuclear localization of Unit7541-GFP.
Figure 6
Figure 6. Novel human cytomegalovirus reading frames based on true ribosome footprints lead to antigens in humans
(A – D) Distribution of fragment lengths mapping to human nuclear CDSes compared to all annotated CMV coding sequences after (A) 5 hours or (B) 72 hours of infection, and of specifically the (C) previously annotated and (D) novel CMV coding sequences after 5 hours of infection. (E, F) Fragment length analysis of human coding sequences compared to (E) previously annotated CMV reading frames and (F) novel CMV annotations. (G) Ribosome fooptirnt organization on beta 2.7 transcript (Stern-Ginossar et al., 2012). (H) ELISPOT assay of human donor T cell responses to novel CMV reading frames along with controls. (I) Quantitation of ELISPOT data.
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