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Erythroid mRNA translation in RPS14 deficiency
the high CAI Fluc was highly repressed but the low CAI Fluc was less affected (Figure 4D and Online Supplementary Figure S4C).
Impact of each mRNA feature on the translation efficiency and transcript stability
To quantify the relative contribution of each character- istic of an mRNA molecule to its translation efficiency, we analyzed the cumulative frequency of the ΔTE. The tran- scripts with the largest translation upregulation were longer and had a lower CAI. Conversely, the transcripts with the largest translation downregulation were those with a highly structured 3’UTR (Figure 5A). Furthermore, the impact of upstream open reading frames (uORF) on translational regulation appeared to be negligible under conditions of RPS14 downregulation (Online Supplementary Figure S5A). To rule out any effect of the 3’UTR or CAI on mRNA stability,30,32,33 we analyzed the mRNA half-life and decay rate in K562 cells. We found that the CAI and 3’UTR energy per base poorly correlated with mRNA decay and half-life measurement (Online Supplementary Figure S5B). Moreover, our transcriptome analysis did not correlate with either mRNA decay or a reduced mRNA half-life, thus excluding a possible global alteration of decay pathways (Online Supplementary Figure S5C). That the cumulative frequency of the differential expression in transcriptomic analysis did not reveal major changes was a definitive indicator of no changes in RNA decay that are dependent on the 3’UTR or 5’UTR struc- ture or the transcript length. Nevertheless, consistent with the previously reported relationship between codon usage and RNA stability,30 we observed a marginally increased decay in low CAI transcripts (Figure 5B).
Proteome analyses confirm the identified rules and point to a post-translational regulation of ribosomal protein
We showed in our initial experiments that global trans- lation was diminished per cell (Figure 1I). Therefore, to investigate the impact of translation selectivity on protein expression, we performed an absolute proteomic quantifi- cation of our UT7/EPO model and normalized the data using histones to avoid growth difference effects and obtain the copy number per cell for each protein (Figure 6A). Because the number of ribosomes associated with a given mRNA depends on the length of this transcript, ana- lyzing the transcripts present on heavy polysomes could favor the identification of the longest mRNAs. Integrating whole proteome and transcriptome analyses excludes this putative bias and provides an indirect measurement of translation and degradation rates. The log2(FC) of the pro- teins was plotted to the log2(FC) of the transcripts to iden- tify components that underwent post-transcriptional regu- lation (Figure 6B and Online Supplementary Table S1). To evaluate post-transcriptional changes, we selected compo- nents having expression that was inversely regulated in the proteome and transcriptome with an FCproteome/FCtranscriptome ratio >1.5 or <1/1.5. First, we confirmed that the post-tran- scriptional changes identified by the proteome analysis were predicted by the ΔTE analysis. At post-transcriptional level, the upregulated components had an increased TE whilst those with downregulated expression had a decreased TE, highlighting that post-transcriptional changes at the proteome level are a direct result of transla- tion selectivity. This also demonstrates that the observed
ΔTE values were not only associated with changes in trans- lational occupancy but also with changes in protein quan- tities (Figure 6C). Furthermore, the post-transcriptionally downregulated components in the proteome were encod- ed by transcripts with a significantly more structured 3’UTR, a shorter length and a higher CAI than the post- transcriptionally upregulated components (Figures 6D-F), whilst the 5’UTR structure had no impact (Figure 6G).
Interestingly, RP transcripts which mainly harbored a short and unstructured 3’UTR were recognized among the post-transcriptionally downregulated components (Online Supplementary Figure S6A). Removing RP from the analysis increased the concordance between the ΔTE and the pro- tein expression level (Figure 6C-F). These results con- firmed that the determinants of translation selectivity pre- dicted by our translatome analysis were relevant. A GO term analysis of the post-transcriptionally regulated com- ponents (Figure 6H) revealed that those which were upregulated, were involved in DNA replication, RNA pro- cessing and splicing (Figure 6H). These terms overlapped those identified by GSEA and GO analyses of the less impacted transcripts in the translatome (Figure 2D and Online Supplementary Figure S2A). Post-transcriptionally downregulated components were found to be involved in translation, rRNA processing and maturation (Figure 6H). Finally, protein expression is controlled by the rules gov- erning the selection of transcripts on the ribosome. We extended our findings by re-analyzing datasets generated previously in lymphoid cell models carrying mutations in the RPS15 gene.34 Those mutations lead to a decrease in the ribosome half-life and content. We observed in our current analysis that mutant cells had a global protein expression imbalance in favor of proteins whose tran- scripts had a low CAI and an unstructured 3’UTR (Online Supplementary Figure S6B).
Codon adaptation index, coding sequence length and thermodynamic characteristics of the untranslated regions are key determinants of translation in normal erythropoiesis
Clinical manifestations of ribosomopathies are linked to the cell-specific impact of mutations. Of note, impaired erythropoiesis may at least be partly related to a transla- tion defect of GATA1.6 To gain further insights into the translational regulation that occurs during normal ery- throid maturation, we investigated the characteristics of the transcripts in the translatome of the K562 cell line, of the proteins expressed in human erythroblasts at different stages of differentiation and in red blood cells, and of the transcripts in the translatome of healthy donor reticulo- cytes.4,13,15,35 We found that a high CAI and a short tran- script length characterized the mRNAs that are translated when erythroid differentiation is induced with hemin in K562 cells or in purified reticulocytes (Figure 7A and B). These parameters also characterized the most expressed proteins in red blood cells (Figure 7C). More generally, a high CAI, short transcript length and an unstructured 5’ and 3’ UTR were the characteristics of transcripts corre- sponding to proteins which show increased expression during the progression of normal erythroid differentiation (Figure 7D and Online Supplementary Figure S7). Our cur- rent results thus indicate that the transcripts encoding pro- teins that accumulate in erythrocytes shared most of the determinants of translation selectivity, which was high- lighted by conditions of limited ribosome availability.
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