{"title":"Inferring translational heterogeneity from Saccharomyces cerevisiae ribosome profiling.","authors":"Pedro do Couto Bordignon, Sebastian Pechmann","doi":"10.1111/febs.15748","DOIUrl":null,"url":null,"abstract":"<p><p>Translation of mRNAs into proteins by the ribosome is the most important step of protein biosynthesis. Accordingly, translation is tightly controlled and heavily regulated to maintain cellular homeostasis. Ribosome profiling (Ribo-seq) has revolutionized the study of translation by revealing many of its underlying mechanisms. However, equally many aspects of translation remain mysterious, in part also due to persisting challenges in the interpretation of data obtained from Ribo-seq experiments. Here, we show that some of the variability observed in Ribo-seq data has biological origins and reflects programmed heterogeneity of translation. Through a comparative analysis of Ribo-seq data from Saccharomyces cerevisiae, we systematically identify short 3-codon sequences that are differentially translated (DT) across mRNAs, that is, identical sequences that are translated sometimes fast and sometimes slowly beyond what can be attributed to variability between experiments. Remarkably, the thus identified DT sequences link to mechanisms known to regulate translation elongation and are enriched in genes important for protein and organelle biosynthesis. Our results thus highlight examples of translational heterogeneity that are encoded in the genomic sequences and tuned to optimizing cellular homeostasis. More generally, our work highlights the power of Ribo-seq to understand the complexities of translation regulation.</p>","PeriodicalId":12261,"journal":{"name":"FEBS Journal","volume":"288 15","pages":"4541-4559"},"PeriodicalIF":5.5000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/febs.15748","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"FEBS Journal","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1111/febs.15748","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/2/22 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 1
Abstract
Translation of mRNAs into proteins by the ribosome is the most important step of protein biosynthesis. Accordingly, translation is tightly controlled and heavily regulated to maintain cellular homeostasis. Ribosome profiling (Ribo-seq) has revolutionized the study of translation by revealing many of its underlying mechanisms. However, equally many aspects of translation remain mysterious, in part also due to persisting challenges in the interpretation of data obtained from Ribo-seq experiments. Here, we show that some of the variability observed in Ribo-seq data has biological origins and reflects programmed heterogeneity of translation. Through a comparative analysis of Ribo-seq data from Saccharomyces cerevisiae, we systematically identify short 3-codon sequences that are differentially translated (DT) across mRNAs, that is, identical sequences that are translated sometimes fast and sometimes slowly beyond what can be attributed to variability between experiments. Remarkably, the thus identified DT sequences link to mechanisms known to regulate translation elongation and are enriched in genes important for protein and organelle biosynthesis. Our results thus highlight examples of translational heterogeneity that are encoded in the genomic sequences and tuned to optimizing cellular homeostasis. More generally, our work highlights the power of Ribo-seq to understand the complexities of translation regulation.
期刊介绍:
The FEBS Journal is an international journal devoted to the rapid publication of full-length papers covering a wide range of topics in any area of the molecular life sciences. The criteria for acceptance are originality and high quality research, which will provide novel perspectives in a specific area of research, and will be of interest to our broad readership.
The journal does not accept papers that describe the expression of specific genes and proteins or test the effect of a drug or reagent, without presenting any biological significance. Papers describing bioinformatics, modelling or structural studies of specific systems or molecules should include experimental data.