Ribonucleoprotein Networks Analyzed by Mutational Profiling (RNP-MaP) is a strategy for probing RNA-protein networks and protein binding sites at a nucleotide resolution. Information about RNP assembly and function can facilitate a better understanding of biological mechanisms. RNP-MaP uses NHS-diazirine (SDA), a hetero-bifunctional crosslinker, to freeze RNA-bound proteins in place. Once the RNA-protein crosslinks are formed, MaP reverse transcription is then conducted to reversely transcribe the protein-bound RNAs as well as introduce mutations at the site of RNA-protein crosslinks. Sequencing results of the cDNAs reveal information about both protein-RNA interaction networks and protein binding sites.
 RNA-MaP involves three major components:
 Long-wavelength UV and SDA reagents are first supplied to living cells to crosslink protein residues with RNA by forming amide bonds between amine groups of lysine (or arginine) residues and succinimidyl esters. Next, cells containing crosslinked RNPs are lysed and the RNA-bound proteins are digested into peptide adducts. MaP reverse transcription is then performed to label the protein-RNA binding sites through peptide adduct-induced mutations. Sequencing of the mutation-containing cDNA product will reveal the mutation sites (or RNP-MaP sites) and the correlations between the RNP-MaP sites are computationally determined using 3-nucleotide windows.
 RNP-MaP sites are defined as protein bound nucleotides. SDA and UV treated and UV only treated sample sequence reads are aligned and mutations are counted using ShapeMapper2 software. The SDA or RNP-MaP reactivity for a nucleotide is the ratio of the crosslinked (SDA and UV treated) mutational frequency to the un-crosslinked (UV only) mutation frequency. Using differential mutational signatures, RNP-MaP sites are identified based on universal normalization factors and thresholds on each RNA nucleotide (U, A, C, and G) derived from analysis of ribonucleoproteins of known structure.
 A nucleotide is identified as a RNP-MaP site if it passes three filters:
 Protein-RNA interactions networks are identified using RNP-MaP correlations since multiple crosslink sites can be detected for a single RNA molecule. RNP-MaP correlations provide a complementary measure of protein binding to RNA independent of RNP-MaP sites. They are identified using a G-test framework known as RingMapper.
 RNP-MaP correlations require a single RNA molecule to form at least two crosslinks and arise from any of three scenarios:
 Using RNP-MaP correlations, a network of protein-RNA interaction sites is found and can then be used for functional analysis.
 CLIP analyzes protein interactions with RNA by combining UV cross-linking and immunoprecipitation. CLIP-based techniques are able to map RNA binding protein binding sites of interest on a genome-wide scale.
 There are many CLIP-based methods including:
 Quantitative mass spectrometry (MS) (or quantitative proteomics) can be used to discover RNA-binding proteins (RBPs) bound to RNA. Labeling MS methods involve the differential use of stable isotope labels or chemical tagging of proteins in samples and controls. This is used to obtain enrichment scores and true binding partners through the ratio of labeled peptides. Label-free MS methods are able to identify proteins in samples and controls. In order to distinguish true binding partners for nonspecific proteins, analytical tools used alongside spectral count data from non-quantitative MS are used to score the probability of a true RBP-RNA interaction
 RNP-MaP can help reveal functionally important RNA-protein binding networks through binding site density and interconnectivity independent of previous knowledge of interacting proteins. Because of the unbiased nature of the analysis, RNP-MaP is able to detect conserved RNA-protein interactions between species.
 RNP-MaP is also able to facilitate the characterization of functionally critical elements in large non-coding RNAs or even viral RNAs.
 As a standalone technique, RNP-MaP cannot be used to determine protein-RNA binding mechanisms or protein identities. In order to do so, RNP-MaP must be used in conjunction with other techniques such as CLIP and mass spectrometry.
 RNP-MaP requires extremely high read-depths for analysis. To identify RNP-MaP sites, 1000x sequencing coverage is required, while RNP-MaP correlation sites require 10,000x sequencing coverage.
 There are severe limitations on the ability to characterize RNP-MaP correlations between distant (>500 nucleotides) RNP-MaP sites. This is due to limitations of MaP reverse transcription processivity (500-600 nucleotides) and sequencing instrument clustering (<1,000 nucleotides).