Human 5' UTR design and variant effect prediction from a massively parallel translation assay.

The ability to predict the impact of cis-regulatory sequences on gene expression would facilitate discovery in fundamental and applied biology. Here we combine polysome profiling of a library of 280,000 randomized 5' untranslated regions (UTRs) with deep learning to build a predictive model that relates human 5' UTR sequence to translation. Together with a genetic algorithm, we use the model to engineer new 5' UTRs that accurately direct specified levels of ribosome loading, providing the ability to tune sequences for optimal protein expression. We show that the same approach can be extended to chemically modified RNA, an important feature for applications in mRNA therapeutics and synthetic biology. We test 35,212 truncated human 5' UTRs and 3,577 naturally occurring variants and show that the model predicts ribosome loading of these sequences. Finally, we provide evidence of 45 single-nucleotide variants (SNVs) associated with human diseases that substantially change ribosome loading and thus may represent a molecular basis for disease.

A common tRNA modification at an unusual location: the discovery of wyosine biosynthesis in mitochondria.

Establishment of the early genetic code likely required strategies to ensure translational accuracy and inevitably involved tRNA post-transcriptional modifications. One such modification, wybutosine/wyosine is crucial for translational fidelity in Archaea and Eukarya; yet it does not occur in Bacteria and has never been described in mitochondria. Here, we present genetic, molecular and mass spectromery data demonstrating the first example of wyosine in mitochondria, a situation thus far unique to kinetoplastids. We also show that these modifications are important for mitochondrial function, underscoring their biological significance. This work focuses on TyW1, the enzyme required for the most critical step of wyosine biosynthesis. Based on molecular phylogeny, we suggest that the kinetoplastids pathways evolved via gene duplication and acquisition of an FMN-binding domain now prevalent in TyW1 of most eukaryotes. These findings are discussed in the context of the extensive U-insertion RNA editing in trypanosome mitochondria, which may have provided selective pressure for maintenance of mitochondrial wyosine in this lineage.

RoboOligo: software for mass spectrometry data to support manual and de novo sequencing of post-transcriptionally modified ribonucleic acids.

Ribosomal ribonucleic acid (RNA), transfer RNA and other biological or synthetic RNA polymers can contain nucleotides that have been modified by the addition of chemical groups. Traditional Sanger sequencing methods cannot establish the chemical nature and sequence of these modified-nucleotide containing oligomers. Mass spectrometry (MS) has become the conventional approach for determining the nucleotide composition, modification status and sequence of modified RNAs. Modified RNAs are analyzed by MS using collision-induced dissociation tandem mass spectrometry (CID MS/MS), which produces a complex dataset of oligomeric fragments that must be interpreted to identify and place modified nucleosides within the RNA sequence. Here we report the development of RoboOligo, an interactive software program for the robust analysis of data generated by CID MS/MS of RNA oligomers. There are three main functions of RoboOligo: (i) automated de novo sequencing via the local search paradigm. (ii) Manual sequencing with real-time spectrum labeling and cumulative intensity scoring. (iii) A hybrid approach, coined 'variable sequencing', which combines the user intuition of manual sequencing with the high-throughput sampling of automated de novo sequencing.