Synonymous mutations do not alter the encoded protein, but they can influence gene expression. To investigate the mechanisms, we engineered a synthetic library of 154 genes that vary randomly at synonymous sites, but all encode the same green fluorescent protein. When expressed in E. coli, GFP protein levels varied 250-fold across the library. GFP mRNA levels, mRNA degradation patterns, and bacterial growth rates also varied, but codon bias did not correlate with gene expression. Rather, the stability of mRNA folding near the ribosomal binding site explained over half the variation in protein levels. In our analysis, mRNA folding and associated rates of translation initiation play a predominant role in shaping expression levels of individual genes, whereas codon bias influences global translation efficiency and cellular fitness.

SummaryMicroRNAs (miRNAs) play key roles in gene regulation, but reliable bioinformatic or experimental identification of their targets remains difficult. To provide an unbiased view of human miRNA targets, we developed a technique for ligation and sequencing of miRNA-target RNA duplexes associated with human AGO1. Here, we report data sets of more than 18,000 high-confidence miRNA-mRNA interactions. The binding of most miRNAs includes the 5′ seed region, but around 60% of seed interactions are noncanonical, containing bulged or mismatched nucleotides. Moreover, seed interactions are generally accompanied by specific, nonseed base pairing. 18% of miRNA-mRNA interactions involve the miRNA 3′ end, with little evidence for 5′ contacts, and some of these were functionally validated. Analyses of miRNA:mRNA base pairing showed that miRNA species systematically differ in their target RNA interactions, and strongly overrepresented motifs were found in the interaction sites of several miRNAs. We speculate that these affect the response of RISC to miRNA-target binding.

Despite their name, synonymous mutations have significant consequences for cellular processes in all taxa. As a result, an understanding of codon bias is central to fields as diverse as molecular evolution and biotechnology. Although recent advances in sequencing and synthetic biology have helped resolve longstanding questions about codon bias, they have also uncovered striking patterns that suggest new hypotheses about protein synthesis. Ongoing work to quantify the dynamics of initiation and elongation is as important for understanding natural synonymous variation as it is for designing transgenes in applied contexts.

SummaryDeep sequencing now provides detailed snapshots of ribosome occupancy on mRNAs. We leverage these data to parameterize a computational model of translation, keeping track of every ribosome, tRNA, and mRNA molecule in a yeast cell. We determine the parameter regimes in which fast initiation or high codon bias in a transgene increases protein yield and infer the initiation rates of endogenous Saccharomyces cerevisiae genes, which vary by several orders of magnitude and correlate with 5′ mRNA folding energies. Our model recapitulates the previously reported 5′-to-3′ ramp of decreasing ribosome densities, although our analysis shows that this ramp is caused by rapid initiation of short genes rather than slow codons at the start of transcripts. We conclude that protein production in healthy yeast cells is typically limited by the availability of free ribosomes, whereas protein production under periods of stress can sometimes be rescued by reducing initiation or elongation rates.

The U3 small nucleolar ribonucleoprotein (snoRNP) plays an essential role in ribosome biogenesis but, like many RNA-protein complexes, its architecture is poorly understood. To address this problem, binding sites for the snoRNP proteins Nop1, Nop56, Nop58, and Rrp9 were mapped by UV cross-linking and analysis of cDNAs. Cross-linked protein-RNA complexes were purified under highly-denaturing conditions, ensuring that only direct interactions were detected. Recovered RNA fragments were amplified after linker ligation and cDNA synthesis. Cross-linking was successfully performed either in vitro on purified complexes or in vivo in living cells. Cross-linking sites were precisely mapped either by Sanger sequencing of multiple cloned fragments or direct, high-throughput Solexa sequencing. Analysis of RNAs associated with the snoRNP proteins revealed remarkably high signal-to-noise ratios and identified specific binding sites for each of these proteins on the U3 RNA. The results were consistent with previous data, demonstrating the reliability of the method, but also provided insights into the architecture of the U3 snoRNP. The snoRNP proteins were also cross-linked to pre-rRNA fragments, with preferential association at known sites of box C/D snoRNA function. This finding demonstrates that the snoRNP proteins directly contact the pre-rRNA substrate, suggesting roles in snoRNA recruitment. The techniques reported here should be widely applicable to analyses of RNA-protein interactions.ribosome synthesis ͉ RNA modification ͉ RNA processing ͉ RNP structure ͉ yeast P roteomic approaches have identified many factors involved in ribosome synthesis in yeast, but we still lack detailed understanding of the architecture of the preribosomes and small nucleolar ribonucleoprotein (snoRNP) complexes that are required for their maturation. Several methods have been described that allow identification of protein-RNA interaction sites in native particles. RNA immunoprecipitation uses formaldehyde to cross-link RNA to proteins (1, 2). Caveats of this method are that formaldehyde also cross-links proteins to proteins and the immunoprecipitation step is performed under semidenaturing conditions, so a positive result does not demonstrate direct RNA-protein interaction, and the spatial resolution of the technique is low. Moreover, formaldehyde and other chemical cross-linkers may not enter the cores of large complexes. This problem can be avoided by cross-linking proteins and RNA with UV light, and several techniques have been reported (3-7).UV-induced protein-RNA cross-links can be detected by primer extension analysis on the RNA and by MALDI-MS on the protein (4). These approaches can detect cross-links on both protein and RNA but primer extension mapping on long RNAs is not practical without prior knowledge of the approximate cross-linking site and MS analyses require up to 50 pmol of RNP (5). The cross-linking and immunoprecipitation (CLIP) method identified protein-RNA interaction sites in mammalian cells by cloning of the covalentlya...

N6-methyladenosine (m6A) is the most abundant base modification found in messenger RNAs (mRNAs). The discovery of FTO as the first m6A mRNA demethylase established the concept of reversible RNA modification. Here, we present a comprehensive transcriptome-wide analysis of RNA demethylation and uncover FTO as a potent regulator of nuclear mRNA processing events such as alternative splicing and 3΄ end mRNA processing. We show that FTO binds preferentially to pre-mRNAs in intronic regions, in the proximity of alternatively spliced (AS) exons and poly(A) sites. FTO knockout (KO) results in substantial changes in pre-mRNA splicing with prevalence of exon skipping events. The alternative splicing effects of FTO KO anti-correlate with METTL3 knockdown suggesting the involvement of m6A. Besides, deletion of intronic region that contains m6A-linked DRACH motifs partially rescues the FTO KO phenotype in a reporter system. All together, we demonstrate that the splicing effects of FTO are dependent on the catalytic activity in vivo and are mediated by m6A. Our results reveal for the first time the dynamic connection between FTO RNA binding and demethylation activity that influences several mRNA processing events.

Mammalian genes are highly heterogeneous with respect to their nucleotide composition, but the functional consequences of this heterogeneity are not clear. In the previous studies, weak positive or negative correlations have been found between the silent-site guanine and cytosine (GC) content and expression of mammalian genes. However, previous studies disregarded differences in the genomic context of genes, which could potentially obscure any correlation between GC content and expression. In the present work, we directly compared the expression of GC-rich and GC-poor genes placed in the context of identical promoters and UTR sequences. We performed transient and stable transfections of mammalian cells with GC-rich and GC-poor versions of Hsp70, green fluorescent protein, and IL2 genes. The GC-rich genes were expressed several-fold to over a 100-fold more efficiently than their GC-poor counterparts. This effect was not due to different translation rates of GC-rich and GC-poor mRNA. On the contrary, the efficient expression of GC-rich genes resulted from their increased steady-state mRNA levels. mRNA degradation rates were not correlated with GC content, suggesting that efficient transcription or mRNA processing is responsible for the high expression of GC-rich genes. We conclude that silent-site GC content correlates with gene expression efficiency in mammalian cells.

Many protein-protein and protein-nucleic acid interactions have been experimentally characterized, whereas RNA-RNA interactions have generally only been predicted computationally. Here, we describe a high-throughput method to identify intramolecular and intermolecular RNA-RNA interactions experimentally by crosslinking, ligation, and sequencing of hybrids (CLASH). As validation, we identified 39 known target sites for box C/D modification-guide small nucleolar RNAs (snoRNAs) on the yeast pre-rRNA. Novel snoRNA-rRNA hybrids were recovered between snR4-5S and U14-25S. These are supported by native electrophoresis and consistent with previously unexplained data. The U3 snoRNA was found to be associated with sequences close to the 3′ side of the central pseudoknot in 18S rRNA, supporting a role in formation of this structure. Applying CLASH to the yeast U2 spliceosomal snRNA led to a revised predicted secondary structure, featuring alternative folding of the 3′ domain and long-range contacts between the 3′ and 5′ domains. CLASH should allow transcriptome-wide analyses of RNA-RNA interactions in many organisms.pre-rRNA | RNA structure | ribosome synthesis | UV cross-linking T he identification of RNA-RNA interactions is essential for detailed understanding of many biological processes. Almost all RNAs must be correctly folded to function, whereas basepairing between different RNA molecules underlies many pathways of RNA metabolism, including pre-mRNA splicing, ribosome synthesis, and the regulation of mRNA stability by microRNAs (miRNAs), among many others. Even for RNAs for which the final structure is known (e.g., rRNA), the folding pathway in precursors is generally unclear. RNA-RNA interactions were previously analyzed by X-ray crystallography, NMR, psoralen cross-linking, and genetics, but all these methods are labor-intensive and typically require prior knowledge of the interacting partners. Because of these technical difficulties, RNA base-pairing is more commonly inferred from a combination of bioinformatic and evolutionary analyses. However, computational methods are applicable only to evolutionarily conserved interactions and provide little information about the physiological context of the interaction.UV cross-linking methods have been developed to map protein interaction sites precisely on RNA molecules, including crosslinking and immunoprecipitation (CLIP) and cross-linking and analysis of cDNAs (CRAC) (1, 2). CRAC analyses have been performed on proteins (Nop1, Nop56, and Nop58) that are associated with all members of the box C/D class of small nucleolar RNAs (snoRNAs). Most box C/D snoRNAs base-pair with the rRNA to select sites of RNA 2′-O-methylation by the methyltransferase fibrillarin (Nop1). In contrast, the U3 snoRNA basepairs to multiple sites on the pre-rRNA. These interactions probably facilitate correct folding of the pre-rRNA and are required for pre-rRNA processing (3, reviewed in refs. 4, 5). PremRNA splicing requires five snRNAs that assemble the complex structure of the spliceosome, with...