Chemical modifications are known to have crucial effects on the biological functions of nucleic acids. While broadly identified in tRNAs and rRNAs, the >150 modifications profiled to date have likewise been discovered in several other classes of RNA (e.g., mRNAs, siRNAs, and miRNAs, among others) where they can affect the structure and intermolecular interactions of the RNA. Understanding the dynamics of RNA modifications is critical to gain insight on their downstream effects; however, characterizing the locations and frequencies of covalent modifications on RNA molecules presents unique challenges. Many types of modified nucleosides have been discovered by thin-layer chromatography or high-performance liquid chromatography, the latter often coupled to mass spectrometry (MS), to glean information about the chemical structure of single nucleosides based on chromatographic retention and mass. While these approaches are critical to understanding which modifications are present within a given RNA sample, they do not yield information about the location of the identified nucleoside modification in the RNA sequence. Similarly, RNA sequencing workflows that leverage next generation sequencing modalities can determine the sequence of a modified oligonucleotide with high accuracy and sensitivity, but because these methods rely on detection of complementary PCR amplification products, the location of the modified nucleotides are lost during analysis. Although biochemical assays have been developed to react with specific modified nucleotides in such a way that they can be detected in subsequent RNA sequencing analysis, these techniques are limited to interrogation of a single modification or motif at a time and are only appropriate for a subset of modified nucleotides. Recent developments in top-down mass spectrometry of RNAs have enabled accurate identification of multiple RNA modifications in tandem while also localizing them to specific nucleotides. Unlike conventional MS methods which most commonly analyze RNA after enzymatic digestion, top-down approaches leverage the capabilities of modern high-resolution MS platforms to ionize, fragment, and detect intact RNA molecules without prior enzymatic digestion. Analogous to top-down approaches in proteomics, analyzing intact RNAs and inducing backbone fragmentation within the mass spectrometer via MS/MS affords extensive molecular fingerprints that may reveal multiple covalent modification co-occurring on each RNA. Advances in top-down analysis of RNAs have focused on improving sample preparation, increasing ionization efficiency, and optimizing fragmentation methods to characterize modifications present on synthetic RNA therapeutics. With respect to sample preparation and ionization issues, on-line desalting workflows have proven to be critical for MS analysis of progressively larger nucleic acids as they address two challenges. First, retention of small adducts (e.g. sodium, ammonium, or potassium ions) on the phosphodiester backbone dilutes signal intensity across the m/z domain owing to production of heterogenous molecular ions. Second, reliable sample introduction methods are critical for high throughput analysis. Micro-or nano-flow HPLC methods address both challenges, enabling fast (<10 min) online desalting and sample introduction while mitigating signal dilution in m/z space. These LC methods use short columns (3 to 5 cm) and often employ ion-pairing or basic mobile phases to prohibit salt adduction during ionization. Effective MS/MS methods are also critical for the successful top-down characterization of nucleic acids. Many modern MS platforms employ several different ion activation techniques amenable to nucleic acids, including collisionally-activated dissociation (CAD), and, more recently, ultraviolet photodissociation (UVPD). Each activation method yields a defined set of fragment ions, typically originating from bond cleavages across the phosphodiester backboneillustrated in Figure -that generate product ions containing either the 3' or 5' terminus, which can be annotated to display identified fragments throughout the primary structure using the type of encoding shown in Figure . CAD of anions primarily produces c and y fragments for RNA or a and w fragments for DNA. UVPD is recently available on select commercial MS platforms and induces fragmentation via irradiation with energetic ultraviolet photons, typically at 213 nm (5.8 eV) or 193 nm (6.4 eV). UVPD preferentially generates d and w fragments along with high-abundance, chargereduced precursors through electron photodetachment. A third MS/MS method, termed activatedelectron photodetachment dissociation (a-EPD), leverages the charge-reduced precursors produced by UV photoactivation and applies supplemental collisional activation, resulting in a mix of fragment ion types (c, d, w, and y fragments). Whether employing CAD, UVPD, or a-EPD, the fragment ions generated encode the sequence of the nucleic acid based on their masses and isotopic distributions, allowing differentiation of any covalent modification with a unique mass. Through this process, top-down mass spectrometry can provide comprehensive information about the identity and location of various covalent modifications in addition to mapping the sequence of the nucleic acid. Given the complexity inherent in top-down MS/MS spectra of even short (<20 nt) oligonucleotides for which fragment ions may exist in multiple charge states, identification and validation of fragment ions is non-trivial. To date, an array of robust software tools have been developed to enable facile processing of MS/MS data for proteomics. These data processing tools often rely on spectral deconvolution algorithms to convert m/z domain data into monoisotopic mass domain data based on charge state determination via isotope spacing, though more recent tools have alternatively identified fragment ions based on their isotopic distributions in the m/z domain. Software tools for processing MS/MS spectra of nucleic acids are less advanced. An early data processing platform for nucleic acid MS/MS data, Simple Oligonucleotide Sequencer, enabled ab initio sequencing of small oligonucleotides. One of the first database search tools developed for RNA analysis was the Ariadne. This approach involved MS-based profiling of RNA components of RNA-protein complexes by analysis of RNase digestion products via a two-step MS/MS search and nucleotide mapping approach. Another foundational software was the pair of OMA (oligonucleotide mass assembler) and OPA (oligonucleotide peak analyzer), specifically developed to support characterization of double-stranded and modified RNAs or DNAs based on fragment ions profiled in pioneering studies. MS/MS data analysis was extended for modified RNAs with RoboOligo, which focused on de novo sequencing of a single digested RNA to map modifications based on c and y fragments produced by CAD. This approach was extended with the development of RNAModMapper, where in silico digestion products of target RNA sequences and their CAD fragments -including c, y, w, a-B, and other neutral loss ions -are generated and identified in LC-MS/MS data sets, enabling localization of RNA modifications on multiple precursors in tandem. An additional approach was developed utilizing NIST spectral library matching of manually annotated RNase T1 digestion products, enhancing analysis throughput. More recently, the Nucleic Acid Search Engine (NASE) platform was released, employing an open-source database searching approach and incorporating optimization for high-resolution mass spectrometers and affording substantial increases in search speed over its predecessors. Pytheas, one of the most recent additions to the RNA-MS software field, incorporated MS/MS search tools into a Python environment for rapid assessment of bottom-up RNA LC-MS/MS data with additional statistical validation by decoy searching. Finally, MIND4OLIGOS recently introduced an algorithm for rapid determination of oligonucleotide monoisotopic mass. Each of these tools has offered substantial progress in the field of RNA MS, leveraging its strengths to characterize biologically relevant molecules. Each of these software methods, however, focuses on the interrogation of LC-MS/MS data of small (typically <30 nt) RNAs produced by digestion with restriction enzymes, limiting their applicability to top-down analyses of nucleic acids.