Translation is one of the fundamental processes of life. It comprises the assembly of polypeptides whose amino acid sequence corresponds to the codon sequence of an mRNA’s ORF. Translation is performed by the ribosome; therefore, in order to understand translation and its regulation we must be able to determine the numbers and locations of ribosomes on mRNAs in vivo. Furthermore, we must be able to examine their redistribution in different physiological contexts and in response to experimental manipulations. The ribosome profiling method provides us with an opportunity to learn these locations, by sequencing a cDNA library derived from the short fragments of mRNA covered by the ribosome. Since its original description, the ribosome profiling method has undergone continuing development; in this article we describe the method’s current state. Important improvements include: the incorporation of sample barcodes to enable library multiplexing, the incorporation of unique molecular identifiers to enable to removal of duplicated sequences, and the replacement of a gel-purification step with the enzymatic degradation of unligated linker.
Synonymous codon choice can have dramatic effects on ribosome speed and
protein expression. Ribosome profiling experiments have underscored that
ribosomes do not move uniformly along mRNAs. We modeled this variation in
translation elongation using a feedforward neural network to predict the
ribosome density at each codon as a function of its sequence neighborhood. Our
approach revealed sequence features affecting translation elongation and
characterized large technical biases in ribosome profiling. We applied our model
to design synonymous variants of a fluorescent protein spanning the range of
translation speeds predicted with our model. Levels of the fluorescent protein
in budding yeast closely tracked the predicted translation speeds across their
full range. We therefore demonstrate that our model captures information
determining translation dynamics
in vivo
, that we can harness
this information to design coding sequences, and that control of translation
elongation alone is sufficient to produce large, quantitative differences in
protein output.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.