Extensive translation of small Open Reading Frames revealed by Poly-Ribo-Seq
Small open reading frames ( smORFs ) of fewer than 100 amino acids exist in eukaryotic genomes in hundreds of thousands , but their annotation has been hindered by their size: short sequences are unable to obtain the high conservation scores that are the accepted indicator of functionality ( Ladoukakis et al . , 2011 ) . This handicap , coupled with the limited numbers of experimentally proven functional smORFs in eukaryotes ( Kastenmayer et al . , 2006; Galindo et al . , 2007; Kondo et al . , 2007; Hanada et al . , 2012; Magny et al . , 2013; Pauli et al . , 2014; reviewed in Andrews and Rothnagel , 2014 ) , has so far precluded the reliable annotation of smORFs as coding sequences . Targeted bioinformatic approaches predict that hundreds of smORFs could be translated and functional in bacteria ( Hemm et al . , 2008 ) , yeast ( Basrai et al . , 1997; Kastenmayer et al . , 2006 ) , plants ( Hanada et al . , 2012 ) and metazoans including Drosophila ( Ladoukakis et al . , 2011 ) , mouse ( Frith et al . , 2006; Crappe et al . , 2013 ) , and humans ( Slavoff et al . , 2013 ) , but this is in contrast to their low rate of detection in biochemical ( proteomic ) ( Falth et al . , 2006; Slavoff et al . , 2013 ) and functional ( genetic ) ( Kumar et al . , 2002 ) screens . Thus , genome-wide assessments of smORF translation in a number of species are needed to determine the actual number of translated smORFs in eukaryotic genomes . The new technique of ribosome profiling has corroborated and expanded the proteomes of yeast ( Ingolia et al . , 2009; Duncan and Mata , 2014; Smith et al . , 2014 ) , mouse ( Ingolia et al . , 2011 ) , zebrafish ( Chew et al . , 2013; Bazzini et al . , 2014 ) , and Drosophila ( Dunn et al . , 2013 ) . Thousands of new translated sequences have been described in each case , whether novel exons of annotated genes , alternative initiation sites , or entire ORFs . However , the application of ribosome profiling outside canonical translated sequences can lead to differing conclusions ( Chew et al . , 2013; Guttman et al . , 2013 ) . The problem remains that a ribosomal footprint cannot always be equated with translation; non-productive binding of single ribosomes to mRNAs and scanning 40S ribosomal subunits can result in footprints , yet do not constitute translation . It has been suggested that some smORFs associate with ribosomes in such a non-productive manner and do not undergo productive translation ( Wilson and Masel , 2011 ) . Moreover , smORF mRNAs are short and present a small target for ribosomal binding and generation of footprints , potentially making traditional ribosome profiling less suitable for the study of smORFs . To distinguish genuine translation events from background , a number of metrics , statistical treatments , and bioinfomatic analyses have been proposed ( Ingolia et al . , 2009; Chew et al . , 2013; Guttman et al . , 2013; Bazzini et al . , 2014 ) . We have taken an alternative approach by enhancing the biochemical foundation of ribosome profiling and developed ‘Poly-Ribo-Seq’ , an improvement to ribosome profiling that should be of use for the study of smORFs and canonical , longer ORFs alike . Instead of profiling all ribosomal-bound mRNAs , we perform ribosome footprinting on polysomal fractions . In this way , mRNAs bound by multiple ribosomes and hence actively translated can be isolated and distinguished from mRNAs bound by sporadic , putatively non-productive single ribosomes or ribosomal subunits . Although this method may overlook very short smORFs that cannot fit multiple ribosomes , this loss should be offset by the increased stringency of discarding false positive footprints . Application of Poly-Ribo-Seq to Drosophila S2 cells reveals extensive translation of thousands of smORFs of two putative types . ‘Longer’ smORFs encode around 80-aa-long peptides , which are translated in the same proportions ( 83% of transcribed coding sequences ) and as efficiently as canonical long ORFs . We nearly double the number of these smORFs shown to be translated , and show that these smORF peptides further resemble canonical proteins in that they are conserved across species , show specific subcellular localisations , and display a specific amino acid composition with the potential to form transmembrane alpha-helices . ‘Dwarf’ smORFs encode peptides in 5′-UTRs and non-coding RNAs , are not detected by gene prediction programs , and are around 20-aa-long . They are less conserved , and translated at lower proportions and efficiencies than canonical proteins . We corroborate these findings by two independent methods and observe smORF peptide expression at or near mitochondria . Extrapolation of our results suggests that thousands of smORFs are translated in higher organisms and that smORFs could have diverse functions , including expression of peptides active in cell membranes .
Given the controversy over ribosome footprinting on lncRNAs ( Chew et al . , 2013; Guttman et al . , 2013 ) , we wanted to improve upon the ribosome profiling method to ensure that the RNAs , on which ribosome footprinting occurs , are undergoing active translation . That is to say they are engaged by polysomes rather than just bound by sporadic , putatively non-productive single ribosomes or ribosomal subunits . We therefore developed an approach for performing ribosome profiling on polysome complexes , using a modified ribosome footprinting method . Polysomal fractionation was used to separate RNAs , depending on the number and type of ribosomes bound to them ( Figure 1B ) . In this way , mRNAs bound by multiple ribosomes and hence actively translated can be isolated and distinguished from mRNAs bound by non-productive 80S ribosomes . This biochemically purified material was then subjected to ribosome profiling , in which the footprinting reaction was optimized for profiling purified polysomal fractions rather than all ribosome-mRNA complexes . To specifically enrich for actively translating single smORF-containing mRNAs , over canonical protein-coding mRNAs , we took advantage of the limited space within a smORF ( ≤303 nt ) for ribosomes to be bound . Ribosomes have been reported to reach densities of 1 ribosome every 80 nt ( Arava et al . , 2003 ) , therefore on a smORF the maximum number of ribosomes associated would be five ribosomes ( one at the start codon and one every 80 nt ) . Although RT-PCR of polysome sucrose gradient fractions confirmed that smORF mRNAs were enriched in small polysomes compared to large polysomes ( Figure 1—figure supplement 1A ) , it suggested that Drosophila smORFs can be bound by up to six ribosomes , perhaps reflecting a tighter packing of ribosomes . We therefore chose to isolate polysomal fractions containing 2–6 ribosomes/mRNA to enrich for smORFs . These small polysomes can also contain mRNAs for canonical longer ORFs , which would be not fully covered by ribosomes and hence translated at less than maximum level ( Figure 1—figure supplement 2 ) . We subjected both small and large polysomal fractions to ribosome profiling separately and performed RNAseq on the total cytoplasmic mRNA as a control ( Figure 1—figure supplement 1B ) . Our ‘Poly-Ribo-Seq’ captured regions of active translation as ∼80% of reads mapped to coding sequences of canonical protein-coding genes ( Supplementary file 1A ) with read densities dropping off before the start and after stop codons ( Figure 1C ) . To quantify the translation of individual coding sequences we considered two metrics: ( 1 ) the ribosomal density in the ORF ( expressed as RPKM ) ( Ingolia et al . , 2009 ) and ( 2 ) coverage of the ORF by ribosome footprints ( 0–1 ) . This metric indicates whether ribosomes bind across the ORF or just in a small fragment of it , which could be due to overlapping or internal ORFs ( Figure 1—figure supplement 2 ) . To be considered translated , we required ribosome densities to be at least 11 . 8 RPKM and footprint coverage of the ORF to be at least 0 . 57 , which are above the 90th percentile of the values we obtained for the 3′-UTRs from canonical coding mRNAs ( see ‘Materials and methods’ for a full explanation of filters and cut-offs ) . These cut-offs are more stringent than previous ribosomal profiling experiments and standard RNAseq practice , and their combination should provide robust identification of transcripts that undergo active translation . To overcome the possible dependence of ribosome density on RNAseq efficiency or transcript abundance ( Guttman et al . , 2013 ) , we also used the relative metric known as translational efficiency ( TE ) , which is the RPKM of ribosome footprints/RPKM of total mRNA control reads ( Ingolia et al . , 2009 ) . We observed that the median TE of all annotated protein-coding transcripts was significantly higher in CDSs compared to 5′- and 3′-UTRs ( Figure 1D ) indicating that ‘Poly-Ribo-Seq’ defines regions of active translation . As previously reported for ribosomal profiling , we observe triplet phasing in the mapping of our Poly-Ribo-Seq reads ( Figure 1—figure supplement 1C ) , reflecting the positioning of ribosomes on codons , which is not globally seen in UTRs ( Figure 1—figure supplement 1D ) . Small and large polysomes showed a marked difference in genome-wide ribosomal densities ( Figure 2A ) , suggesting that these two fractions contain mRNAs translated at different levels . Small polysomes contain mRNAs encoding long ORFs , but these have lower TE than when isolated from large polysomes ( Table 2 ) , confirming that they were bound by fewer ribosomes . As intended , Poly-Ribo-Seq detected smORFs with translation signatures , and these were enriched in small polysomes , which contained double the number and all of the smORFs detected in large polysomes ( Figure 2C ) . The low smORF TE values in large polysomes are similarly consistent with low levels of smORF mRNAs being present in large polysomal complexes . However , the TE of smORFs from small polysomes is similar to the TE of long ORFs from large polysomes , indicating that smORFs can be translated at similar levels to standard protein-coding ORFs ( Table 2; Figure 1—figure supplement 2 ) . 10 . 7554/eLife . 03528 . 007Figure 2 . Poly-Ribo-Seq reveals translation of smORFs . ( A ) Ribosome footprinting densities ( RPKM ) from small polysomes correlate poorly with large polysomes ( whereas two replicates of total cytoplasmic mRNA controls do , see Figure 1—figure supplement 1B ) . ( B ) Ribosome footprinting densities ( RPKM ) from small polysomes correlate highly between two biological replicates ( R2 = 0 . 83 ) . ( C ) All 106 smORFs detected in large polysomes ( blue ) were also present in the 191 detected in small polysomes ( purple ) . smORF footprints are much more abundant in small polysomes , as indicated by a higher TE value . ( D ) High coincidence of annotated smORFs detected as translated in three different Poly-Ribo-Seq experiments . Small polysome extensive experiment probes most deeply with 224 smORFs detected as translated ( small polysomes: purple , small polysomes extensive: yellow , -rRNA: turquoise ) . ( E ) Numbers and proportions of transcribed ORFs , which are translated , according to Poly-Ribo-Seq data ( translated: green , untranslated: blue ) . The proportion of annotated smORFs translated is similar to that of standard CDSs . 121 annotated smORFs are newly detected as translated , plus 2708 uORFs and 313 smORFs from ncRNAs . ( F ) Venn diagram showing overlap between Poly-Ribo-Seq ( dark green ) , our mass spectrometry experiments ( purple ) and Peptide Atlas proteomic data ( red ) . DOI: http://dx . doi . org/10 . 7554/eLife . 03528 . 00710 . 7554/eLife . 03528 . 008Figure 2—figure supplement 1 . Poly-Ribo-Seq reveals translation of smORFs . ( A ) Results of Poly-Ribo-Seq experiments with all ( -rRNA: turquoise ) , large ( blue ) , and small ( purple ) polysomes showing the number of canonical protein-coding ORFs ( longer than 100 aa ) translated and the overlap between experiments . ( B ) Venn diagram showing the overlap in the detection of translation between Poly-Ribo-Seq ( dark green ) and proteomic experiments ( pink ) . Median RPKMs from Poly-Ribo-Seq are indicated . DOI: http://dx . doi . org/10 . 7554/eLife . 03528 . 00810 . 7554/eLife . 03528 . 009Table 2 . Summary of median TEsDOI: http://dx . doi . org/10 . 7554/eLife . 03528 . 009Median TESmall polysomesLarge polysomesAnnotated smORFs1 . 1310 . 265standard ORFs0 . 8291 . 1105′-UTR0 . 3550 . 5663′-UTR0 . 1620 . 196uORFs0 . 2760 . 347ncRNA smORFs0 . 3840 . 000Median translational efficiency for ORFs in small and large polysomal fractions . Altogether 191 annotated smORFs passed the cut-off values to be deemed translated in this initial Poly-Ribo-Seq experiment . This is ∼70% of the smORFs transcribed in S2 cells in the total mRNA controls ( Figure 2D , small polysomes ) . To ensure that initial Poly-Ribo-Seq experiments sequenced to an adequate depth and to potentially extend the catalogue of translated smORFs , we repeated the experiment but exclusively sequenced small polysomes . This extensive small polysome profiling yielded nearly four times the number ORF-mapping reads obtained in the previous small polysome profiling ( Supplementary file 1A ) and detected translation of 224 smORFs ( Figure 2D ) expanding the number from both experiments to 227 , which is 83% of smORFs we observed transcribed in S2 cells ( Figure 2E ) . The genome-wide distribution of ribosome densities in two independent Poly-Ribo-Seq experiments was strongly correlated ( R2 = 0 . 83 ) , suggesting that Poly-Ribo-Seq is highly reproducible ( Figure 2B ) . The majority of reads in both our experiments and previous ribosomal profiling consist of rRNA sequences released during footprinting ( Supplementary file 1A; Ingolia et al . , 2011 ) . This reduces the depth of profiling and could preclude the detection of further smORFs . Therefore , we designed rRNA-depletion beads for use during footprint extraction ( ‘Materials and methods’ , Supplementary file 2 ) , which produced a marked improvement in the ratio of reads mapping to mRNAs ( Supplementary file 1A ) and increased the total number of ORFs detected ( Figure 2—figure supplement 1A , −rRNA ) but only expanded our overall catalogue of putatively translated smORFs by one ( Figure 2D ) . The results of the three independent experiments are highly overlapping as 80% of putative translated smORFs were detected in all three data sets ( Figure 2D ) . By combining the three experiments , we provide evidence that 228 smORFs are translated out of 274 transcribed in S2 cells ( 83% ) , which is very similar to the proportion of standard length protein-coding ORFs translated ( 81% ) ( Figure 2E ) . These similar proportions may indicate the extent of translational regulation in S2 cells . Altogether this data almost doubles the previous repertoire of translated smORFs in Drosophila from 164 to 285 ( 164 previously corroborated [Figure 1A] and 121 new translated smORFs ) . The high overlap of our experiments suggests that the results do not arise from artefactual random sampling of smORFs , but most likely from the detection of the bona-fide population of annotated smORFs translated in S2 cells . To confirm this and independently validate our data , we compared our results with peptidomics data ( Peptide Atlas , Brunner et al . , 2007 ) . Poly-Ribo-Seq increases nearly fourfold the number of smORFs with evidence of translation in S2 cells from 59 ( Peptide Atlas ) to 228 ( Poly-Ribo-Seq ) . Poly-Ribo-Seq detects 86% of smORFs with Peptide Atlas evidence in S2 cells ( 51 out of 59 smORFs; Figure 2F ) , whilst only 8 smORFs , which have Peptide Atlas evidence are not shown to be translated by Poly-Ribo-Seq . Detection of small peptides requires specific peptidomic methods ( Boerjan et al . , 2010; Slavoff et al . , 2013 ) , and this could have limited the number of smORF peptides detected in the generic proteomic experiments of Peptide Atlas . Therefore , we specifically searched for smORF peptides by performing mass spectrometry on two biological replicates of S2 cells after gel purifying small proteins 5 to 15 KDa in size , which corresponds to peptides predicted to be 45 to 130 aa in length . We detected a total of 60 annotated smORF peptides , of which 40 are not detected in Peptide Atlas S2 data sets ( Figure 2F ) , thus bringing the combined pool of smORFs peptides detected by proteomics in S2 cells to 99 ( Figure 2—figure supplement 1B ) . Despite this increase , Poly-Ribo-Seq was still more extensive . Poly-Ribo-Seq revealed 228 smORFs as translated , including 90 of the 99 in the combined proteomics pool ( Figure 2—figure supplement 1B ) , and 59 of the 60 peptides detected by us ( Figure 2F ) . The Poly-Ribo-Seq RPKM values of smORFs detected by peptidomics are over three times as high as those that are not ( Figure 2—figure supplement 1B ) , suggesting that mass spectrometry detects peptides arising from the most highly translated smORFs , as also observed by other authors ( Brunner et al . , 2007; Bazzini et al . , 2014 ) . To further validate the results of our smORF Poly-Ribo-Seq , we designed a peptide-tagging transfection assay . smORF coding sequences were tagged with a C-terminal FLAG tag lacking its own start codon . The constructs contained the full smORF 5′-UTR ( which includes the Kozak and other sequences regulating translation [Kozak , 2005] ) ( Figure 3—figure supplement 1A ) . The resulting construct was transfected into S2 cells , where any FLAG signal would therefore be the result of smORF translation ( Figure 3—figure supplement 1A , B ) . Transfection and staining of S2 cells with these FLAG-tagged smORFs confirmed the translation of all 12 smORFs tested , which exhibit a range of translational indicators ( Figure 3A , B; Table 3 ) and peptidomics evidence , indicating that even lower levels of translation can give rise to smORF peptides detectable by this tagging method . Immunoblotting confirmed the expected sizes of the tagged peptides ( Figure 3—figure supplement 1C ) . Tagged peptides exhibit distinct subcellular localisations , which are suggestive of different peptide functions ( Figure 3A , B; Table 3 ) . Six smORFs display a reticular distribution resembling mitochondria , an inference supported by their co-localization with the mitochondrial marker Mitotracker Red ( Figure 3A and Figure 3—figure supplement 1D , E; Table 3 ) and the available information from homologues of two ‘corroborated’ smORFs in this group , CG32230 and CG14482 ( Tripoli et al . , 2005 ) . Six smORFs exhibited other types of anisotropic cytoplasmic localisation , similarly to ER-expressed Sarcolamban smORF ( Magny et al . , 2013 ) , indicating that they may localise to other cytoplasmic compartments ( Figure 3B and Figure 3—figure supplement 1D , E; Table 3 ) . 10 . 7554/eLife . 03528 . 010Figure 3 . Validation of smORF translation by tagging assay . ( A–D ) Ribosome footprints from small polysomes ( pink ) and mRNA reads ( grey ) mapped to smORFs , along with transcript and ORF models of ( A ) CG7630 , ( B ) CG33774 , ( C ) CR30055 ( ncRNA ) , and ( D ) FBtr0072084_1 ( uORF ) . Corresponding transfection assays in S2 cells are shown ( FLAG antibody: green , F-actin stained with phalloidin: red , scale bars = 5 μm ) together with Poly-Ribo-Seq metrics ( RPKM , coverage and TE ) . Distribution of each peptide ( reticular , other cytoplasmic or limited ) is indicated . DOI: http://dx . doi . org/10 . 7554/eLife . 03528 . 01010 . 7554/eLife . 03528 . 011Figure 3—figure supplement 1 . Validation of smORF translation by tagging assay . ( A ) Schematic of the transfection construct into which smORF 5′-UTRs and ORFs ( no stop codon ) were cloned under the Actin promoter , such as to be fused in frame to a C-terminal FLAG tag , with its own AUG start codon mutated to GCG . ( B ) Transfection negative controls , plasmid with no ORF ( nor AUG ) , plasmid with the full-length tal transcript ( minus 3′-UTR ) with ORF-B tagged with FLAG , which has previously been shown not to be translated ( Galindo et al . , 2007 ) , and a plasmid containing a putative smORF that is transcribed but not translated according to our Poly-Ribo-Seq ( Uhg2-ORF1 ) . ( C ) Immunoblot showing translation of FLAG-tagged smORFs ( Table 3 ) corresponding to predicted sizes , along with β- tubulin loading control . ( D ) Different subcellular localisations of FLAG-tagged smORFs ( green ) corroborated by double staining with Mitotracker Red ( red ) : “mitochondrial” , “other cytoplasmic” and “limited” ( scale bar = 5 μm ) . ( E ) Correlation analysis of colocalisation between FLAG-tagged smORF peptides and Mitotracker Red , error bars represent SD from three experiments . ( F ) 50% of S2-cell translated smORFs show function in previous RNAi screens ( Flymine ) . ( G ) Translation of FLAG-tagged pncr009:3L ( ncRNA ) ORFs 1 , 2 , and 3 in transfection assay with translational metric values shown ( FLAG antibody: green , F-actin stained with phalloidin: red , scale bars = 5 μm ) . ( H ) Immunoblot showing detection of FLAG-tagged ORFs from pncr009:3L and CR30055 with predicted sizes ( Table 4 ) , along with β-tubulin loading control . ( I ) Translation of FLAG-tagged uORFs FBtr0072210_1 and FBtr0081720_1 in transfection assays with translational metric values shown ( FLAG antibody: green , F-actin stained with phalloidin: red , scale bars = 5 μm ) . DOI: http://dx . doi . org/10 . 7554/eLife . 03528 . 01110 . 7554/eLife . 03528 . 012Figure 3—figure supplement 2 . Poly-Ribo-Seq reveals translation of ORFs in ncRNAs . ( A ) Read density plot showing phasing of ribosome footprinting reads in the frame of smORFs within CR30055 and pncr009:3L detected as translated and confirmed by FLAG immunofluorescence translation assay . ( B ) Correlation of reads obtained by ORFs after Poly-Ribo-Seq ( y axis ) with reads obtained by sequencing of polysomal fractions before ribosome footprinting ( x axis ) . The correlation is much stronger for canonical long ORFs and putative smORFs ( grey ) than for ncRNA ORFs ( red ) . Many ncRNA ORFs below the 11 . 8 RPKM cut-off used to ascertain translation ( green dotted line ) can show association with polysomes ( high Polysomal RNA RPKM ) , thus translation of ORFs in ncRNAs does not simply stem from non-coding association with polysomes . DOI: http://dx . doi . org/10 . 7554/eLife . 03528 . 01210 . 7554/eLife . 03528 . 013Table 3 . Summary of tagged annotated smORFsDOI: http://dx . doi . org/10 . 7554/eLife . 03528 . 013LocalizationPeptidomic evidence# aaRPKMCoverageTEPhast ConsCG32230MitochondrialYes83539 . 21 . 003 . 050 . 54CG14482MitochondrialYes57600 . 01 . 001 . 090 . 72CG44242MitochondrialYes70152 . 90 . 971 . 750 . 66CG7630MitochondrialYes90702 . 21 . 001 . 050 . 64CG33199MitochondrialNo7995 . 51 . 001 . 170 . 59CG32582MitochondrialNo5216 . 50 . 572 . 820 . 51sclAOther cytoplasmicNA28NANANANACG12384Other cytoplasmicYes96205 . 61 . 001 . 370 . 71CG33774Other cytoplasmicNo40115 . 31 . 001 . 130 . 73CG33170Other cytoplasmicNo7184 . 20 . 840 . 750 . 60CG34200LimitedYes52331 . 71 . 001 . 660 . 54CG32267LimitedYes4982 . 50 . 971 . 130 . 70CG33155LimitedNo6033 . 80 . 640 . 880 . 67tal-BNoneNA49NANANANADetails of the Poly-Ribo-Seq and transfection translation assay results for the FLAG-tagged smORFs , with RPKM , coverage and TE values . Previously corroborated smORFs ( according to Figure 1A ) are in bold . Scl is a positive control and tal-B is a negative control , but both are not endogenously transcribed in S2 cells , hence ‘NA’ Polysomal Ribo-Seq metrics and Peptidomic evidence . The putative functionality of smORF peptides is further supported by over half of the translated smORFs having revealed a function in high-throughput S2 cell RNAi screens in previous studies ( Schmidt et al . , 2012; Figure 3—figure supplement 1F ) . The biological relevance of smORFs is also implied by the transcription of 196 of these translated smORFs in embryos ( Supplementary file 1B ) . 88 of these smORFs are transcribed throughout the whole of embryogenesis , which might be indicative of a basic cellular or housekeeping role , whereas 47 have stage-specific expression , perhaps indicative of a developmental role . Non-annotated smORFs were also scrutinized by Poly-Ribo-Seq . Many putative ncRNAs have been annotated as such because no long ORFs have been detected , but they can still contain smORFs . We looked for evidence of translation in 6438 ORFs that initiate with an AUG start codon within ncRNAs . Our total cytoplasmic mRNA data indicate that 125 ncRNA transcripts ( containing 918 different ORFs ) are transcribed and present in the cytoplasm of S2 cells . 313 smORFs in these transcripts appear translated by Poly-Ribo-Seq ( Figure 2E ) , but ncRNA smORFs behaved differently from protein-coding and smORF genes . The median translation efficiency of these putative smORFs within ncRNA genes is lower than for canonical genes and annotated smORFs , and in fact is similar to UTRs ( Table 2 ) . In addition , we could not observe nor obtain peptidomics corroboration for the encoded peptides , and the FLAG signal is limited for the majority of such smORFs tested in the transfection assay ( Figure 3C , Figure 3—figure supplement 1G ) . Yet a sizeable fraction ( 34% ) of non-coding RNA smORFs displayed Poly-Ribo-Seq metrics above our cut-off values indicating translation ( Figure 2E; Table 4 ) and some can display FLAG and Western blot signal similar to annotated smORFs ( Figure 3C , Figure 3—figure supplement 1G , H; Table 4 ) . Further , these positive-testing smORFs from non-coding RNAs show codon read-phasing ( Figure 3—figure supplement 2A ) . These translation events do not necessarily represent ‘background’ translation of non-coding RNAs associated with polysomes . The comparison of ribosomal footprinting reads with reads resulting from the sequencing of RNA from polysomal fractions before footprinting ( as in polysomal profiling ) shows a high correlation for canonical coding sequences as expected ( Smith et al . , 2014 ) , but not for non-coding RNAs , where high RNASeq polysomal counts do not necessarily result in significant footprinting ( Figure 3—figure supplement 2B ) . Altogether , our results suggest that a proportion of these so-called non-coding RNA genes actually contain smORFs that are actively translated in S2 cells . 10 . 7554/eLife . 03528 . 014Table 4 . Summary of tagged smORFs from non-coding RNAs and uORFsDOI: http://dx . doi . org/10 . 7554/eLife . 03528 . 014smORFLocalizationPeptidomic evidence# aaRPKMCoverageTEPhastConspncr009:3L ORF1Other cytoplasmicNo21135 . 71 . 000 . 290 . 44pncr009:3L ORF2LimitedNo3064 . 70 . 580 . 630 . 49pncr009:3L ORF3LimitedNo3347 . 80 . 780 . 230 . 59CR30055 ORF1Not testedNo1215 . 20 . 711 . 240 . 49CR30055 ORF2MitochondrialNo5326 . 10 . 660 . 830 . 52CR30055 ORF3Not testedNo3654 . 60 . 852 . 900 . 55CR30055 ORF4LimitedNo1730 . 00 . 64NA0 . 54CR30055 ORF5LimitedNo5628 . 00 . 853 . 70 . 55Uhg2-ORF 1NoneNo3610 . 50 . 270 . 830 . 54FBtr 0072084_1ReticularNo1446 . 80 . 764 . 350 . 52FBtr 0072210_1Other cytoplasmicNo1397 . 70 . 924 . 340 . 48FBtr 0081720_1LimitedNo11121 . 31 . 002 . 390 . 55Details of the Poly-Ribo-Seq and transfection translation assay results for the FLAG-tagged smORFs translated from non-coding RNAs and uORFs , with RPKM , coverage and TE values . Upstream short ORFs , or uORFs , have been described in more than 50% of annotated mammalian transcripts encoding canonical , long ORFs ( Fritsch et al . , 2012 ) . We identified 14 , 881 uORFs with AUG start codons , within 11 , 587 5′-UTRs of 28 , 529 FlyBase annotated transcripts . 9069 of these uORFs were transcribed in S2 cells and of these 2708 ( 30% ) are footprinted by ribosomes ( Figure 2E ) . Similarly to smORFs in putative non-coding RNAs , translated uORFs display lower median TE than canonical ORFs and translated smORFs ( Table 2 ) , and they are not detected by peptidomics , altogether suggesting low abundance of the encoded peptides . However , tagging of uORFs can occasionally show similar signal to annotated smORFs ( Figure 3D , Figure 3—figure supplement 1I ) . We scrutinised our set of annotated translated smORFs for bioinformatic markers , which might further suggest function of smORF peptides . Firstly , we used phastCons ( Siepel et al . , 2005 ) that measures conservation between 12 insect species . We examined the phastCons values in intergenic sequences and canonical long protein-coding sequences ( Figure 4A ) and obtained a cut-off value of 0 . 55 separating them ( 10% FDR ) . 93% of S2-translated smORFs have phastCons scores above this threshold ( median = 0 . 66 ) , indicating a conservation level similar to that of canonical long-ORFs , and hence , a similar level of functionality for the coding sequences . 10 . 7554/eLife . 03528 . 015Figure 4 . Bioinformatic indicators of smORFs . ( A ) Distribution of phastCons scores for intergenic regions , standard length protein-coding CDSs ( longer than 100 aa ) , S2 cell-translated annotated smORFs , and all annotated smORFs , with fitted normal curves . Green dotted lines indicate the 90th percentile of intergenic phastCons scores ( 0 . 55 ) . ( B ) Relative abundance of particular amino acids in proteins ( random expected: black , all CDSs: purple , all annotated smORFs: yellow , and translated smORFs: red ) . ( C and D ) Proportion of ( C ) S2-cell translated ( 32% ) and ( D ) all smORFs ( 32% ) predicted to contain transmembrane α helices ( TMHMM ) . ( E and F ) Frequency distribution of smORF peptide lengths for ( E ) translated and ( F ) all annotated smORFs with medians shown by red dotted line . DOI: http://dx . doi . org/10 . 7554/eLife . 03528 . 01510 . 7554/eLife . 03528 . 016Figure 4—figure supplement 1 . Bioinformatic indicators of smORFs . ( A ) Relative abundance of all amino acids in ORFs , ( random: grey , all CDS: purple , all annotated smORFs: yellow , and translated annotated smORFs: red ) . ( B ) Enrichment of GO molecular function terms ( GOrilla ) within translated annotated smORFs in S2 cells when compared to translated standard protein-coding ORFs . Main overrepresented terms are structural consitituents of ribosome ( p = 3 . 28E-4 ) , oxidoreductase activity and transmembrane transporter activity ( p = 2 . 77E-5 ) . ( C–D ) Frequency distribution of peptide lengths , phastCons , and relative abundance of particular amino acids of translated ( C ) uORFs and ( D ) ncRNA ORFs . Red dotted lines indicate the median amino acid lengths and green dotted lines indicate the 90th percentile cut-off from phastCons of intergenic regions , 0 . 55 ( Figure 4A ) . DOI: http://dx . doi . org/10 . 7554/eLife . 03528 . 016 As a further indicator of smORF translation , we studied the amino acid composition of translated smORFs , compared to canonical long proteins and expected random usage ( Figure 4B ) . Annotated smORFs display a lower than random usage of arginine , which is a hallmark of translated proteins ( King and Jukes , 1969 ) . However , they also display differential usage of several amino acids , which are characteristic of alpha-helices in canonical proteins , being enriched for lysine and phenylalanine , and depleted of serine ( Chou and Fasman , 1974; Figure 4B , Figure 4—figure supplement 1A ) . This finding was corroborated by an abundance of putative transmembrane alpha-helix motifs , in about a third of translated smORFs ( Figure 4C ) and all predicted smORFs ( Figure 4D ) compared to the expected 20% observed in canonical proteins ( Krogh et al . , 2001 ) . This is in agreement with similar findings in bacteria ( Hemm et al . , 2008 ) and suggests that smORFs may represent a source of uncharacterised transmembrane peptides . An enrichment for molecular GO terms such as membrane transporter activity in annotated smORFs ( Figure 4—figure supplement 1B ) , and the subcellular localisations we observe for half of the tagged smORFs , are also consistent with these findings . The 555 annotated smORFs not transcribed in S2 cells , including 505 smORFs with uncorroborated translation , share the bioinformatic characteristics of the smORFs detected as translated by Poly-Ribo-Seq including: average peptide length ( Figure 4E–F ) ; amino acid usage ( Figure 4B , Figure 4—figure supplement 1A ) ; and abundance of putative transmembrane alpha-helices ( Figure 4C , D ) . Therefore , our results showing translation and possible peptide function for 83% of the smORFs transcribed in S2 cells could be extrapolated to this wider pool , potentially bringing the number of smORFs encoding functional peptides in Drosophila to around 700 . The peptides encoded by uORFs and ncRNAs did not behave bioinformatically as smORFs and canonical long CDS , and thus we cannot easily extrapolate from our results to the uORFs and ncRNAs not transcribed in S2 cells . No indicator ( phastCons , size , aa composition ) was able to distinguish translated uORFs and ncRNAs from intergenic or random sequences ( Figure 4—figure supplement 1C–D ) . Even though our Poly-Ribo-Seq detects translation of these uORFs and ncRNAs , perhaps the function of these smORFs is not mediated by their encoded peptides , or at least is compatible with a shorter , more variable and less canonical amino acid sequence ( ‘Discussion’ ) . It appears that Poly-Ribo-Seq detects translation of two types of smORF: ( a ) ‘longer’ smORFs that are efficiently translated producing peptides ∼80 aa possessing bioinformatic hallmarks of peptide function; and ( b ) ‘dwarf’ smORFs translated from ncRNAs and 5′-UTRs , which are in general shorter ( ∼20 aa ) , less efficiently translated , and missing such bioinformatic and molecular markers .
We have developed an improvement to ribosome profiling , which we term Poly-Ribo-Seq , to ensure that footprinted mRNA sequences represent regions of active translation rather than non-productive events . Using Poly-Ribo-Seq , we have specifically profiled the translation of smORFs in Drosophila S2 cells , using a purification of small polysomes to enrich for smORFs . Poly-Ribo-Seq doubles the number of annotated smORFs in Drosophila S2 cells with evidence of translation from 107 to 228 . Translated smORFs seem similar to canonical proteins , both in terms of the fraction actually translated ( over 80% in both cases , Figure 2E ) and the level of translation ( as revealed by RPKM , coverage , and TE ) . Extrapolating the proportion of smORFs translated in S2 cells ( 83% ) to the uncorroborrated 544 smORFs transcribed elsewhere , indicates that altogether around 700 annotated smORFs could be translated , which can be tested in further Poly-Ribo-Seq experiments . The annotation of the Drosophila genome is unusual in its high proportion of annotated smORFs , which is double that of vertebrate genomes ( Table 1 ) . Thus , examination of smORF translation in vertebrate genomes is likely to significantly increase the proteome of these species . Consistent with this prediction the translation of 190 smORFs has been detected in one such experiment in zebrafish ( Bazzini et al . , 2014 ) . Extrapolation of these two sets of results in flies and zebrafish strongly suggests that hundreds of smORFs are translated in higher organisms , including in humans and other mammals . While bioinformatics can be useful in unearthing smORF candidates , ultimately experimental evidence and full functional characterisation is the only way to ascertain the translation and function of each individual smORF . Our data confirm the tentative annotation of Drosophila smORFs and expand our understanding of smORF translation . Firstly , we corroborate the translation of 121 smORFs for which no previous conclusive evidence existed . Secondly , we fail to detect the translation of some 46 transcribed smORFs , most of which have no evidence of translation , and which ( pending new profiling experiments from further biological sources ) , could be either translationally regulated or non-functional . Thirdly , we also detect the translation of a high number of non-annotated smORFs from 5′-UTRs and non-coding RNAs . 313 ncRNA smORFs and 2708 uORFs are detected as translated by Poly-Ribo-Seq , although perhaps at low levels , as indicated by their low median TEs . Given the small proportion of non-coding RNAs we detect in S2 cells , it is unclear if the numbers observed here can be extrapolated to the smORFs found in all other ncRNAs . However , we notice that if extrapolated to other animals , such as mammals including humans , even a low number of translated ncRNAs would be significant . The human genome contains some 32 , 000 transcripts currently annotated as long non-coding RNAs ( Volders et al . , 2013 ) , and a fraction around 44% of long-non-coding RNAs have been detected in the cytoplasm ( Derrien et al . , 2012 ) . If these cytoplasmic lncRNAs were corroborated and translated in the same proportion as we find here in Drosophila ( some 34% ) , there could be thousands of human peptides awaiting detection and characterisation . The number swells to many thousands when adding uORFs . The small size of both uORF and ncORF peptides may hinder their detection by mass spectrometry , as in the case of peptides translated by the Drosophila genes tal and scl ( unpublished observation ) , and so absence of proteomic detection ( or absence of functional data , see below ) should not be used to disprove their translation . Poly-Ribo-Seq detects almost all peptides detected by proteomics , but is two to three times more extensive . Furthermore , Poly-Ribo-Seq can define the whole of the translated ORF as opposed to isolated micropeptides detected by peptidomics . Though available proteomic evidence has been useful in confirming the depth of Poly-Ribo-Seq , it is clear that currently peptidomics is not as sensitive as ribosome profiling . High peptide translation level seems a critical factor ( but likely not the only one ) favouring detection by mass spectrometry . However , the combination of Poly-Ribo-Seq and peptidomics could produce interesting data on peptide stability and degradation . The putative function of smORFs and their encoded peptides is a separate issue from their translation , just as the transcription of thousands of apparently non-coding RNAs is an accepted fact separated from their , as yet , not fully understood function . Our present work is concerned with proving smORF translation , as a first step to eventually uncovering their true function . However , the function of a number of smORFs has been identified in animal and plants ( reviewed in Andrews and Rothnagel , 2014 ) , and our data allow for some speculations . We observe that most annotated and translated smORFs have conservation levels similar to canonical proteins and have so far displayed functionality in RNAi tests in some 50% of the cases . They encode peptides of around 80 aa with a high proportion of transmembrane alpha-helix motifs , in agreement with their overall pattern of amino acid composition . Their bioinformatic indicators ( conservation , size , aa usage , and transmembrane motifs ) appear similar in the 505 uncorroborated smORFs not transcribed in S2 cells , suggesting that , if translated , some 700 smORFs might encode peptides with similar functional potential . The corroborated smORFs display a variety of functions as antibacterial peptides ( Lemaitre and Hoffmann , 2007 ) , cell signals ( Pueyo and Couso , 2008 ) , cytoskeletal regulators ( Djakovic et al . , 2006 ) , and other regulators of canonical proteins ( Hanyu-Nakamura et al . , 2008; Magny et al . , 2013 ) . GO term enrichment analysis shows that the most abundant terms amongst previously corroborated smORFs are ribosome constituents , oxidoreductase activity , and transporter activity ( Figure 4—figure supplement 1B ) . The last two imply an association with biological membranes , and it is thus interesting that amongst uncorroborated smORFs , the frequency of predicted transmembrane alpha-helix motifs is the highest . Furthermore , the observed tagged smORF peptide localization to mitochondria is also compatible with these findings . We surmise that hundreds of small , membrane-associated peptides are awaiting characterisation , and they may alter our understanding of many cellular and organismal processes of biological and medical relevance . We expect that these peptides would interact with canonical proteins as their regulators ( Magny et al . , 2013 ) , as their size limits their structural capabilities; though , such capabilities could be expanded by oligomerization . The main described function of most uORFs is to regulate translation of downstream long ORFs , either interfering with the translation of the downstream ORF , or collecting ribosomes in order to promote it . The translated uORF peptide ( and hence its aa sequence ) can be irrelevant ( [Child et al . , 1999; Kulkarni et al . , 2011] reviewed in Kozak , 2005; Andrews and Rothnagel , 2014 ) . Such a cis-regulatory role would fit with the low TE and the high sequence variability ( low phastCons scores ) observed for uORFs . However , we do not observe an overall positive or negative correlation between the translation of uORFs and that of their main downstream ORF ( unpublished observation ) , as perhaps could be expected under this cis-regulatory model . Validating uORF function is difficult , since much of the current functional ( genetics ) data is based on conditions ( gene deficiencies , promotor mutations , RNAi ) that knock-out whole transcripts , that is , both the short uORF peptide and the downstream long-canonical protein . The smORFs in putative long non-coding RNAs with ribosomal signatures might reveal either coding potential , a non-coding association with ribosomes , or a dual function as coding and non-coding for these transcripts . Again , standard genetic techniques are unable to distinguish between these possibilities . This group of smORFs has the potential to encode functional peptides , as shown by the genes tal and scl , that were previously annotated as putative non-coding RNAs . These genes encode peptides as short as 11 and 28 aa with important functions in development and physiology ( Galindo et al . , 2007; Kondo et al . , 2007; Magny et al . , 2013 ) . In the case of Scl , a transmembrane alpha-helical structure was corroborated ( Magny et al . , 2013 ) . Further , a manual study of their homologies identified their conservation in distant species . Thus , a case-by-case bioinformatic and experimental examination of ncRNA smORFs may reveal unknown numbers of new bioactive peptides . Altogether our data indicate that thousands of smORFs are translated in metazoan genomes . However , they also suggest the existence of two broad types of translated smORFs . The ‘longer’ smORFs produce conserved 80 aa-long peptides whose translation efficiencies resemble those of canonical proteins and with functions biased towards an association with cell membranes . The ‘dwarf’ smORFs are mostly found in 5′-UTRs and non-coding RNAs , are not detected by gene prediction programs , and on average encode peptides of some 20 aa-long . They are also less conserved , translated at lower efficiencies , and of unclear function as yet .
S2 cells were grown under standard conditions in Schneiders medium with 10% FBS . S2 cells were treated with cycloheximide ( Sigma , St Louis , MO ) at 100 μg/ml for 3 min at RT before harvesting . The cells were pelleted , washed ( 1X PBS , 100 μg/ml cycloheximide ) , and resuspended in lysis buffer; 50 mM Tris–HCl pH8 , 150 mM NaCl , 10 mM MgCl2 , 1 mM DTT , 1% NP40 , 100 µg/ml cycloheximide , Turbo DNase ( Life Technologies , Carlsbad , CA ) , RNasin Plus RNase Inhibitor ( Promega , Carlsbad , CA ) , cOmplete Protease Inhibitor ( Roche ) . Nuclei were removed , and cytoplasmic lysates were loaded onto sucrose gradients and subjected to ultracentrifugation . Gradients were pumped out , their absorbance at 254 nm plotted and fractionated . We purified mRNAs in small polysomes , away from monosomes ( 80S ) , ribosomal subunits ( 40S , 60S ) , and large polysomes . Footprinting was performed overnight at 4°C with RNaseI ( Life Technologies ) , stopped with SUPERase·In RNase inhibitor ( Life Technologies ) and precipitated . mRNA from total cytoplasmic lysate was purified using oligo ( dT ) Dynabeads ( Life Technologies ) and fragmented by alkaline hydrolysis . 28–34 nt ribosome footprints and 50–80 nt mRNA fragments were gel purified and prepared as previously described ( Ingolia et al . , 2009 , 2011 , 2012 ) for Next Generation Sequencing . Libraries were sequenced on Illumina HiSeq2000 and MiSeq machines with 50 bp SingleEnd read protocol . To generate ssDNA complementary to Drosophila rRNA , PCRs were performed using 5′ biotinylated reverse primers ( Supplementary file 2 ) . A 5′ biotinlyated oligo complementary to 2S rRNA and rRNA PCR products were bound to magnetic streptavidin beads ( Life Technologies ) and their second strands washed away . Two rounds of 50 µl rRNA beads were used to deplete rRNA prior to reverse transcription . RNA from sucrose gradient fractions was precipitated with isopropanol and 0 . 3 M NaCl . Resuspended pellets were treated with Turbo DNaseI ( Life Technologies ) , extracted with phenol/chloroform and re-precipitated . cDNA was synthesised MMLV reverse transcriptase ( Promega ) and subjected to PCR with mRNA specific primers and Taq Polymerase ( Qiagen , Venio , Netherlands ) . Sequencing reads were clipped , trimmed , and aligned to an rRNA and tRNA reference using Bowtie , discarding the rRNA and tRNA alignments and collecting unaligned reads . Unaligned reads were mapped to FlyBase ( Release 5 . 50 ) using TopHat . We only retained reads that mapped uniquely , but allowed up to two mismatches . Profiles of ribosome footprints across a transcript were constructed by quantifying the number of footprint reads aligned at each position within the feature of interest . Ribosome density was computed by scaling read counts for each feature-by-feature length and by the total number of genome-aligned reads ( Ingolia et al . , 2009 ) . Footprint coverage estimated the percentage of each feature covered by ribosome footprints using the BEDTools coverageBed command . We applied several filters to ascertain translation . We have taken the reads in the 3′-UTRs of mRNAs encoding canonical coding sequences ( longer than 100 aa ) , from the small polysomal fraction , as representing ‘background’ , that is likely non-coding sequences from mRNAs that are lowly translated . We obtained the RPKM and coverage values from this canonical 3′-UTR signal , and use their 90th percentile values as preliminary cut-offs for accepting translation of coding sequences . These values are 11 . 8 RPKM and 0 . 40 coverage . Superimposed onto these we use two additional corrections: first , we raised the coverage cut-off to 0 . 57 because ‘dwarf’ smORFs of less than 20 aa ( Figure 4—figure supplement 1C ) containing a single ribosomal binding ‘site’ could still appear as 0 . 56 covered ( 32 nt/57 nt ) ; second , we introduce the need for an ORF to obtain at least five reads in a single experiment to be considered translated , to avoid inflation of very few reads by the RPKM metric in such dwarf smORFs . Translation efficiency ( TE ) was calculated as ribosome footprint density ( RPKM ) /mRNA-seq read density ( RPKM ) in the feature . As the TE score is not a reliable estimator at low expression levels , we computed a TE score only for those features that had significant mRNA expression above a randomised genomic background ( p < 0 . 01 ) . To analyse framing , ribosome-protected fragments ( RPF ) were aligned to transcript cooordinates . For a given open reading frame , the corresponding P-site position of filtered RPF reads ( 28–32 nt ) was designated as follows: +12 offset for 28 and 29 nt , +13 for 30 to 31 nt , and +14 for 32 nt RPF ( Chew et al . , 2013; Bazzini et al . , 2014 ) . We identified uORFs and ncORFs longer than 10 aa with an AUG start codon followed by an in-frame stop codon within the annotated 5′-UTRs and ncRNA transcripts , using the emboss getorf program . To exclude the possibility that the ribosome occupancy observed in 5′-UTRs was due to the presence of such upstream ORFs , we created a modified transcript that contained all regions except the putative uORFs for all our analysis on 5′-UTRs . phastCons scores for 171 , 317 alignment blocks were downloaded from UCSC Genome Browser . We computed percentage overlap between the phastCons block and our feature of interest and estimated mean phastCons values . Lists of peptide CDS coordinates with protein identifiers ( FlyBase peptide ID ) were downloaded from Peptide Atlas database ( http://www . peptideatlas . org ) and compared to FlyBase predicted smORF peptide sequences . Prediction of transmembrane alpha-helices was performed using TMHMM ( http://www . cbs . dtu . dk/services/TMHMM/ ) . In house perl scripts ( available in Supplementary file 3 ) calculated amino acid composition of CDS . For the random control , we followed King and Jukes ( 1969 ) . We took all FlyBase transcript sequences and calculated the nucleotide composition of this pool; from this we estimated the likely amino acid usage based on the nucleotide composition of the respective codons . RNAi screen data were accessed through Flymine ( http://www . flymine . org/ ) , and GO term enrichment was calculated by GOrilla ( http://cbl-gorilla . cs . technion . ac . il/ ) ( Eden et al . , 2009 ) . The 5′-UTR and CDS of putative smORFs were cloned by PCR from S2 cell cDNA into pENTR/D-TOPO ( Invitrogen ) and then into pAWF ( http://emb . carnegiescience . edu/labs/murphy/Gateway%20vectors . html# ) , whose ATG start codon was mutated to GCG by site-directed mutagenesis . S2 cells were plated on acid-treated coverslips and transfected with plasmid DNA using Xtreme Gene HP ( Roche ) . After 48 hr , the cells were fixed for 20 min with 4% formaldehyde , washed with 1X PBS , 0 . 1% Triton X–100 ( PBS-T ) , blocked with PBS-T 2% wt/vol BSA before immunostaining with primary mouse anti-FLAG M2 antibody ( Sigma ) at 1/1000 and secondary anti-mouse FITC ( Jackson , West Grove , PA ) at 1/400 . For subcellular localisation experiments , cells were incubated for 30 min with Rhodamine-Phalloidin ( Life Technologies ) to highlight F-actin . All transfections were incubated for 10 min with Hoechst ( Sigma ) according to manufacturer's instructions for nuclei staining and mounted with Vectashield ( Vector Labs , Burlingame , CA ) . For Mitotracker experiments , 48 hr after transfection cells were incubated in 500 nM Mitotracker Red CMXRos ( Life Technologies ) for 45 min . Imaging was conducted using a Zeiss 63X Plan Apochromat Oil Immersion lens on the LSM510 Axioskop 2 . For correlation analysis Z-stack images were taken with slice interval of 0 . 15 μm , and ImageJ plugin ‘Manders Coefficients’ was used to calculate correlation coefficient of FLAG to Mitotracker signal with at least 15 cells per replicate , with three replicate transfections . Cells were harvested 48 hr post transfection , washed with 1X PBS , resuspended in Tricine Sample buffer ( Bio-Rad , Hercules , CA ) ( 2 . 5% vol/vol βME ) and run on 16% Tris-Tricine gels . Immunoblots were incubated with primary antibody: 1:10 , 000 anti-FLAG M2 ( Sigma ) and 1:500 anti-β-tubulin E7 ( DSHB , Iowa City , IA ) , and then secondary 1:10 , 000 goat anti-mouse HRP ( Santa Cruz , Dallas , TX ) . Immunoblots were developed with ECL Prime Chemiluminescent Detection Reagent ( GE Healthcare , Little Chalfont , UK ) . S2 cells were lysed in 0 . 075% SDS , 1X c0mplete Protease Inhibitor Cocktail ( Roche ) with three rounds of freeze thawing and clarified . Total protein ( 1X Tricine Loading buffer , 2 . 5% vol/vol βME ) was run on 10–20% MiniProtean Tris-Tricine Gels ( Bio-Rad ) and the 5–15 KDa region excised . Mass spectrometry was performed by Cambridge Centre for Proteomics ( University of Cambridge , UK ) using in-gel trypsin digestion and LC-ESI-MS/MS using an Orbitrap Velos Instrument ( Thermo Fisher Scientific ) with the following parameters: 2 missed Trypsin cleavages , 25 ppm Precursor mass error , 0 . 8 Da fragment mass tolerance , carbamidomethylation of cysteine as a fixed and methionine oxidation as a variable modification . Spectra were matched against Drosophila melanogaster ( 5 . 55 ) proteome using generic Mascot algorithm .
Thousands of small Open Reading Frames ( smORFs ) with the potential to encode small peptides of fewer than 100 amino acids exist in our genomes . However , the number of smORFs actually translated , and their molecular and functional roles are still unclear . In this study , we present a genome-wide assessment of smORF translation by ribosomal profiling of polysomal fractions in Drosophila . We detect two types of smORFs bound by multiple ribosomes and thus undergoing productive translation . The ‘longer’ smORFs of around 80 amino acids resemble canonical proteins in translational metrics and conservation , and display a propensity to contain transmembrane motifs . The ‘dwarf’ smORFs are in general shorter ( around 20 amino-acid long ) , are mostly found in 5′-UTRs and non-coding RNAs , are less well conserved , and have no bioinformatic indicators of peptide function . Our findings indicate that thousands of smORFs are translated in metazoan genomes , reinforcing the idea that smORFs are an abundant and fundamental genome component .
To produce a protein , a stretch of DNA must first be transcribed to produce a molecule of messenger RNA ( mRNA ) . The genetic information copied from the DNA is then read three letters at a time , in groups called codons . Each codon either encodes a particular amino acid to be added into a protein or provides further instructions: ‘start codons’ mark the beginning of a protein; ‘stop codons’ mark its end . The DNA between these two points is called an open reading frame ( or ORF ) —however , not all ORFs produce proteins . Most proteins are made of several hundred amino acids , but the genomes of animals contain thousands of ORFs that would generate much smaller proteins made of fewer than 100 amino acids , if they were translated . It is , however , unclear how many of these small ORFs are converted into mRNA molecules and functional proteins . Ribosomes are large molecular machines that translate the code in mRNA molecules and join together the appropriate amino acids in the right order to make a protein . Ribosome profiling is a technique that identifies which mRNA molecules are translated into proteins by determining the sequences of all the mRNA molecules bound to ribosomes at a particular moment . The mRNA sequences can then be compared with the sequence of the whole genome to work out which ORFs they correspond to . Ribosome profiling has been used to detect translated small ORFs , but the method yields a relatively high false positive rate as some mRNAs can bind to ribosomes without being translated . To better detect small protein-producing ORFs , Aspden et al . developed a technique based on ribosome profiling called Poly-Ribo-Seq . The method takes advantage of the fact that during active translation , clusters of multiple ribosomes , called polysomes , bind mRNAs . Poly-Ribo-Seq isolates these polysomes and determines the sequence bound by each of the ribosomes , thereby reducing the number of false positives . Applying Poly-Ribo-Seq to cells from the fruit fly Drosophila allowed Aspden et al . to identify two types of short ORF . The first type codes for proteins that are around 80 amino acids long and are translated with the same efficiency as larger ORFs . The sequences of these ORFs are found in other species , match at least in part sequences of known functional ORFs , and the proteins produced are found in specific locations inside cells . These small proteins may contribute to membrane integrity or function . Together , these properties suggest that these mRNAs create functional small proteins . The second pool consists of very small ORFs ( ‘dwarf smORFs’ ) that code for around 20 amino acids , which are not translated so often and do not show many similarities with other species . As the findings of Aspden et al . suggest that a large fraction of Drosophila small ORFs are translated into proteins , the next challenge will be to determine the roles of these small proteins in cells .