Ribosome profiling of mouse embryonic stem cells reveals the complexity and dynamics of mammalian proteomes.
Cell, 2011/11/11;147(4):789-802.
Ingolia NT[1], Lareau LF, Weissman JS
Affiliations
PMID: 22056041DOI: 10.1016/j.cell.2011.10.002
Impact factor: 66.85
Abstract
The ability to sequence genomes has far outstripped approaches for deciphering the information they encode. Here we present a suite of techniques, based on ribosome profiling (the deep sequencing of ribosome-protected mRNA fragments), to provide genome-wide maps of protein synthesis as well as a pulse-chase strategy for determining rates of translation elongation. We exploit the propensity of harringtonine to cause ribosomes to accumulate at sites of translation initiation together with a machine learning algorithm to define protein products systematically. Analysis of translation in mouse embryonic stem cells reveals thousands of strong pause sites and unannotated translation products. These include amino-terminal extensions and truncations and upstream open reading frames with regulatory potential, initiated at both AUG and non-AUG codons, whose translation changes after differentiation. We also define a class of short, polycistronic ribosome-associated coding RNAs (sprcRNAs) that encode small proteins. Our studies reveal an unanticipated complexity to mammalian proteomes.
MeSH terms
Algorithms; Animals; Artificial Intelligence; Embryoid Bodies; Embryonic Stem Cells; Genomics; Harringtonines; High-Throughput Nucleotide Sequencing; Kinetics; Mice; Open Reading Frames; Peptide Chain Initiation, Translational; Protein Biosynthesis; RNA; Ribosomes; Sequence Analysis, RNA
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