Ribonucleic acid (RNA) is composed primarily of four canonical building blocks. In addition, more than 170 modifications contribute to its stability and function. Metabolites like nicotinamide adenine dinucleotide (NAD) were found to function as 5'-cap structures of RNA, just like 7-methylguanosine (m7G). The identification of NAD-capped RNA sequences was first made possible by NAD captureSeq, a multistep protocol for the specific targeting, purification, and sequencing of NAD-capped RNAs, developed in the authors' laboratory in the year 2015. In recent years, a number of NAD-RNA identification protocols have been developed by researchers around the world. They have enabled the discovery and identification of NAD-RNAs in bacteria, archaea, yeast, plants, mice, and human cells, and they play a key role in studying the biological functions of NAD capping. We introduce the four parameters of yield, specificity, evaluability, and throughput and describe to the reader how an ideal NAD-RNA identification protocol would perform in each of these disciplines. These parameters are further used to describe and analyze existing protocols that follow two general methodologies: the capture approach and the decapping approach. Capture protocols introduce an exogenous moiety into the NAD-cap structure in order to either specifically purify or sequence NAD-capped RNAs. In decapping protocols, the NAD cap is digested to 5'-monophosphate RNA, which is then specifically targeted and sequenced. Both approaches, as well as the different protocols within them, have advantages and challenges that we evaluate based on the aforementioned parameters. In addition, we suggest improvements in order to meet the future needs of research on NAD-modified RNAs, which is beginning to emerge in the area of cell-type specific samples. A limiting factor of the capture approach is the need for large amounts of input RNA. Here we see a high potential for innovation within the key targeting step: The enzymatic modification reaction of the NAD-cap structure catalyzed by ADP-ribosyl cyclase (ADPRC) is a major contributor to the parameters of yield and specificity but has mostly seen minor changes since the pioneering protocol of NAD captureSeq and needs to be more stringently analyzed. The major challenge of the decapping approach remains the specificity of the decapping enzymes, many of which act on a variety of 5'-cap structures. Exploration of new decapping enzymes or engineering of already known enzymes could lead to improvements in NAD-specific protocols. The use of a curated set of decapping enzymes in a combinatorial approach could allow for the simultaneous detection of multiple 5'-caps. The throughput of both approaches could be greatly improved by early sample pooling. We propose that this could be achieved by introducing a barcode RNA sequence before or immediately after the NAD-RNA targeting steps. With increased processing capacity and a potential decrease in the cost per sample, protocols will gain the potential to analyze large numbers of samples from different growth conditions and treatments. This will support the search for biological roles of NAD-capped RNAs in all types of organisms.
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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Evidence ID | Analyze ID | File | Description |
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