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RNA binding proteins (RBPs) regulate nearly all post-transcriptional processes within cells. To fully understand RBP function, it is essential to identify their in vivo targets. Standard techniques for profiling RBP targets, such as crosslinking immunoprecipitation (CLIP) and its variants, are limited or suboptimal in some situations, e.g. when compatible antibodies are not available and when dealing with small cell populations such as neuronal subtypes and primary stem cells. This review summarizes and compares several genetic approaches recently designed to identify RBP targets in such circumstances. TRIBE (targets of RNA binding proteins identified by editing), RNA tagging, and STAMP (surveying targets by APOBEC-mediated profiling) are new genetic tools useful for the study of post-transcriptional regulation and RBP identification. We describe the underlying RNA base editing technology, recent applications, and therapeutic implications.

We used a relatively new method, HyperTRIBE, to identify in vivo RNA targets of the translation inhibitor 4E-BP., 4E-BP (eIF4E-BP) represses translation initiation by binding to the 5′ cap–binding protein eIF4E and inhibiting its activity. Although 4E-BP has been shown to be important in growth control, stress response, cancer, neuronal activity, and mammalian circadian rhythms, it is not understood how it preferentially represses a subset of mRNAs. We successfully used HyperTRIBE (targets of RNA binding proteins identified by editing) to identify in vivo 4E-BP mRNA targets in both Drosophila and mammals under conditions known to activate 4E-BP. The protein associates with specific mRNAs, and ribosome profiling data show that mTOR inhibition changes the translational efficiency of 4E-BP TRIBE targets more substantially compared to nontargets. In both systems, these targets have specific motifs and are enriched in translation-related pathways, which correlate well with the known activity of 4E-BP and suggest that it modulates the binding specificity of eIF4E and contributes to mTOR translational specificity.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are two related neurodegenerative diseases that present with similar TDP-43 pathology in patient tissue. TDP-43 is an RNA-binding protein which forms aggregates in neurons of ALS and FTD patients as well as in a subset of patients diagnosed with other neurodegenerative diseases. Despite our understanding that TDP-43 is essential for many aspects of RNA metabolism, it remains obscure how TDP-43 dysfunction contributes to neurodegeneration. Interestingly, altered neuronal dendritic morphology is a common theme among several neurological disorders and is thought to precede neurodegeneration. We previously found that both TDP-43 overexpression (OE) and knockdown (KD) result in reduced dendritic branching of cortical neurons. In this study, we used TRIBE (targets of RNA-binding proteins identified by editing) as an approach to identify signaling pathways that regulate dendritic branching downstream of TDP-43. We found that TDP-43 RNA targets are enriched for pathways that signal to the CREB transcription factor. We further found that TDP-43 dysfunction inhibits CREB activation and CREB transcriptional output, and restoring CREB signaling rescues defects in dendritic branching. Finally, we demonstrate, using RNA sequencing, that TDP-43 OE and KD cause similar changes in the abundance of specific messenger RNAs, consistent with their ability to produce similar morphological defects. Our data therefore provide a mechanism by which TDP-43 dysfunction interferes with dendritic branching, and may define pathways for therapeutic intervention in neurodegenerative diseases.

RNA-binding proteins (RBPs) accompany RNA from birth to death, affecting RNA biogenesis and functions. Identifying RBP-RNA interactions is essential to understanding their complex roles in different cellular processes. However, detecting in vivo RNA targets of RBPs, especially in a small number of discrete cells, has been a technically challenging task. We previously developed a novel technique called TRIBE (targets of RNA-binding proteins identified by editing) to overcome this problem. TRIBE expresses a fusion protein consisting of a queried RBP and the catalytic domain of the RNA-editing enzyme ADAR (adenosine deaminase acting on RNA) (ADARcd), which marks target RNA transcripts by converting adenosine to inosine near the RBP binding sites. These marks can be subsequently identified via high-throughput sequencing. In spite of its usefulness, TRIBE is constrained by a low editing efficiency and editing-sequence bias from the ADARcd. Therefore, we developed HyperTRIBE by incorporating a previously characterized hyperactive mutation, E488Q, into the ADARcd. This strategy increases the editing efficiency and reduces sequence bias, which markedly increases the sensitivity of this technique without sacrificing specificity. HyperTRIBE provides a more powerful strategy for identifying RNA targets of RBPs with an easy experimental and computational protocol at low cost, that can be performed not only in flies, but also in mammals. The HyperTRIBE experimental protocol described below can be carried out in cultured Drosophila S2 cells in 1 week, using tools available in a common molecular biology laboratory; the computational analysis requires 3 more days.

We previously developed TRIBE, a method for the identification of cell-specific RNA binding protein targets. TRIBE expresses an RBP of interest fused to the catalytic domain (cd) of the RNA editing enzyme ADAR and performs Adenosine-to-Inosine editing on RNA targets of the RBP. However, target identification is limited by the low editing efficiency of the ADARcd. Here we describe HyperTRIBE, which carries a previously characterized hyperactive mutation (E488Q) of the ADARcd. HyperTRIBE identifies dramatically more editing sites, many of which are also edited by TRIBE but at a much lower editing frequency. HyperTRIBE therefore more faithfully recapitulates the known binding specificity of its RBP than TRIBE. In addition, separating RNA binding from the enhanced editing activity of the HyperTRIBE ADAR catalytic domain sheds light on the mechanism of ADARcd editing as well as the enhanced activity of the HyperADARcd.

Background The molecular history of animal evolution from single-celled ancestors remains a major question in biology, and little is known regarding the evolution of cell cycle regulation during animal emergence. In this study, we conducted a comprehensive evolutionary analysis of CDK and cyclin proteins in metazoans and their unicellular relatives. Results Our analysis divided the CDK family into eight subfamilies. Seven subfamilies (CDK1/2/3, CDK5, CDK7, CDK 20, CDK8/19, CDK9, and CDK10/11) are conserved in metazoans and fungi, with the remaining subfamily, CDK4/6, found only in eumetazoans. With respect to cyclins, cyclin C, H, L, Y subfamilies, and cyclin K and T as a whole subfamily, are generally conserved in animal, fungi, and amoeba Dictyostelium discoideum. In contrast, cyclin subfamilies B, A, E, and D, which are cell cycle-related, have distinct evolutionary histories. The cyclin B subfamily is generally conserved in D. discoideum, fungi, and animals, whereas cyclin A and E subfamilies are both present in animals and their unicellular relatives such as choanoflagellate Monosiga brevicollis and filasterean Capsaspora owczarzaki, but are absent in fungi and D. discoideum. Although absent in fungi and D. discoideum, cyclin D subfamily orthologs can be found in the early-emerging, non-opisthokont apusozoan Thecamonas trahens. Within opisthokonta, the cyclin D subfamily is conserved only in eumetazoans, and is absent in fungi, choanoflagellates, and the basal metazoan Amphimedon queenslandica. Conclusions Our data indicate that the CDK4/6 subfamily and eumetazoans emerged simultaneously, with the evolutionary conservation of the cyclin D subfamily also tightly linked with eumetazoan appearance. Establishment of the CDK4/6-cyclin D complex may have been the key step in the evolution of cell cycle control during eumetazoan emergence.