RNA is often altered post-transcriptionally by the covalent modification of particular nucleotides; these modifications are known to modulate the structure and activity of their host RNAs. The recent discovery that an RNA methyl-6 adenosine demethylase (FTO) is a risk gene in obesity has brought to light the significance of RNA modifications to human biology. These noncanonical nucleotides, when converted to cDNA in the course of RNA sequencing, can produce sequence patterns that are distinguishable from simple base-calling errors. To determine whether these modifications can be detected in RNA sequencing data, we developed a method that can not only locate these modifications transcriptome-wide with single nucleotide resolution, but can also differentiate between different classes of modifications. Using small RNA-seq data we were able to detect 92% of all known human tRNA modification sites that are predicted to affect RT activity. We also found that different modifications produce distinct patterns of cDNA sequence, allowing us to differentiate between two classes of adenosine and two classes of guanine modifications with 98% and 79% accuracy, respectively. To show the robustness of this method to sample preparation and sequencing methods, as well as to organismal diversity, we applied it to a publicly available yeast data set and achieved similar levels of accuracy. We also experimentally validated two novel and one known 3-methylcytosine (3mC) sites predicted by HAMR in human tRNAs. Researchers can now use our method to identify and characterize RNA modifications using only RNA-seq data, both retrospectively and when asking questions specifically about modified RNA.

The functional structure of all biologically active molecules is dependent on intra- and inter-molecular interactions. This is especially evident for RNA molecules whose functionality, maturation, and regulation require formation of correct secondary structure through encoded base-pairing interactions. Unfortunately, intra- and inter-molecular base-pairing information is lacking for most RNAs. Here, we marry classical nuclease-based structure mapping techniques with high-throughput sequencing technology to interrogate all base-paired RNA in Arabidopsis thaliana and identify ∼200 new small (sm)RNA–producing substrates of RNA–DEPENDENT RNA POLYMERASE6. Our comprehensive analysis of paired RNAs reveals conserved functionality within introns and both 5′ and 3′ untranslated regions (UTRs) of mRNAs, as well as a novel population of functional RNAs, many of which are the precursors of smRNAs. Finally, we identify intra-molecular base-pairing interactions to produce a genome-wide collection of RNA secondary structure models. Although our methodology reveals the pairing status of RNA molecules in the absence of cellular proteins, previous studies have demonstrated that structural information obtained for RNAs in solution accurately reflects their structure in ribonucleoprotein complexes. Furthermore, our identification of RNA–DEPENDENT RNA POLYMERASE6 substrates and conserved functional RNA domains within introns and both 5′ and 3′ untranslated regions (UTRs) of mRNAs using this approach strongly suggests that RNA molecules are correctly folded into their secondary structure in solution. Overall, our findings highlight the importance of base-paired RNAs in eukaryotes and present an approach that should be widely applicable for the analysis of this key structural feature of RNA.

The secondary structure of RNA is necessary for its maturation, regulation, processing, and function. However, the global influence of RNA folding in eukaryotes is still unclear. Here, we use a high-throughput, sequencing-based, structure-mapping approach to identify the paired (double-stranded RNA [dsRNA]) and unpaired (single-stranded RNA [ssRNA]) components of the Drosophila melanogaster and Caenorhabditis elegans transcriptomes, which allows us to identify conserved features of RNA secondary structure in metazoans. From this analysis, we find that ssRNAs and dsRNAs are significantly correlated with specific epigenetic modifications. Additionally, we find key structural patterns across protein-coding transcripts that indicate that RNA folding demarcates regions of protein translation and likely affects microRNA-mediated regulation of mRNAs in animals. Finally, we identify and characterize 546 mRNAs whose folding pattern is significantly correlated between these metazoans, suggesting that their structure has some function. Overall, our findings provide a global assessment of RNA folding in animals.

We have measured the electronic circular dichroism (ECD) of the ferri- and ferro-states of several natural cytochrome c derivatives (horse heart, chicken, bovine, and yeast) and the Y67F mutant of yeast in the region between 300 and 750 nm. Thus, we recorded the ECD of the B- and Q-band region as well as the charge-transfer band at approximately 695 nm. The B-band region of the ferri-state displays a nearly symmetric couplet at the B0-position that overlaps with a couplet 790 cm-1 higher in energy, which we assigned to a vibronic side-band transition. For the ferro-state, the couplet is greatly reduced, but still detectable. The B-band region is dominated by a positive Cotton effect at energies lower than B0 that is attributed to a magnetically allowed iron-->heme charge-transfer transition as earlier observed for nitrosyl myoglobin and hemoglobin. The Q-band region of the ferri-state is poorly resolved, but displays a pronounced positive signal at higher wavenumbers. This must result from a magnetically allowed transition, possibly from the methionine ligand to the dxy-hole of Fe3+. For the ferro-state, the spectra resolve the vibronic structure of the Qv-band. A more detailed spectral analysis reveals that the positively biased spectrum can be understood as a superposition of asymmetric couplets of split Q0 and Qv-states. Substantial qualitative and quantitative differences between the respective B-state and Q-state ECD spectra of yeast and horse heart cytochrome c can clearly be attributed to the reduced band splitting in the former, which results from a less heterogeneous internal electric field. Finally, we investigated the charge-transfer band at 695 nm in the ferri-state spectrum and found that it is composed of at least three bands, which are assignable to different taxonomic substates. The respective subbands differ somewhat with respect to their Kuhn anisotropy ratio and their intensity ratios are different for horse and yeast cytochrome c. Our data therefore suggests different substate populations for these proteins, which is most likely assignable to a structural heterogeneity of the distal Fe-M80 coordination of the heme chromophore.

We measured the temperature-dependent electronic circular dichroism (ECD) spectra of AX, XA, and XG dipeptides in D2O. The spectra of all XA and AX peptides indicate a substantial population of the polyproline II (PPII) conformation, while the ECD spectra of LG, KG, PG, and AG were found to be quantitatively different from the alanine-based dipeptides. Additional UV absorption data indicate that the ECD spectra of the XG peptides stem from electronic coupling between the peptide and the C-terminal group, and that spectral differences reflect different orientations of the latter. We also measured the 1H NMR spectra of the investigated dipeptides to determine the 3JHalphaNH coupling constants for the C-terminal residue. The observed temperature dependence of the ECD spectra and the respective room-temperature 3JHalphaNH coupling constants were analyzed by a two-state model encompassing PPII and a beta-like conformation. The PPII propensity of alanine in the XA series is only slightly modulated by the N-terminal side chain, and is larger than 50%. As compared to AA, XA peptides containing L, P, S, K V, E, T, and I all cause a relative stabilization of the extended beta-strand conformation. The PPII fractions of XA peptides varied between 0.64 for AA and 0.58 for DA, whereas the PPII fractions of AX peptides were much lower. From the investigated AX peptides, only AL and AQ showed the expected PPII propensity. We found that AT, AI, and AV clearly prefer an extended beta-strand conformation. A quantitative comparison of AA, AAA, and AAAA revealed a hierarchy AAAA > AAA approximately AA for the PPII population, in agreement with predictions from MD calculations and results from Raman optical activity studies (McColl et al. J. Am. Chem. Soc. 2004, 126, 5076).