Locus-specific interrogation of the genome using programmable CRISPR-based technologies is tremendously useful in dissecting the molecular basis of target gene function and modulating its downstream output. Although these tools are widely utilized in recruiting genetically encoded functional proteins, display of small molecules using this technique is not well developed due to inadequate labeling technologies. Here, we report the development of a modular technology, sgRNA-Click (sgR-CLK), which harnesses the power of bioorthogonal click chemistry for remodeling CRISPR to display synthetic molecules on target genes. A terminal uridylyl transferase (TUTase) was repurposed to construct an sgRNA containing multiple minimally invasive bioorthogonal clickable handles, which served as a Trojan horse on CRISPR-dCas9 system to guide synthetic tags site-specifically on chromatin employing copper-catalyzed or strainpromoted click reactions. Our results demonstrate that sgR-CLK could provide a simplified solution for site-directed display of small molecules to study as well as modulate the function of gene targets.

RNA dimerization is the noncovalent association of two human immunodeficiency virus-1 (HIV-1) genomes. It is a conserved step in the HIV-1 life cycle and assumed to be a prerequisite for binding to the viral structural protein Pr55Gag during genome packaging. Here, we developed functional analysis of RNA structure-sequencing (FARS-seq) to comprehensively identify sequences and structures within the HIV-1 5′ untranslated region (UTR) that regulate this critical step. Using FARS-seq, we found nucleotides important for dimerization throughout the HIV-1 5′ UTR and identified distinct structural conformations in monomeric and dimeric RNA. In the dimeric RNA, key functional domains, such as stem-loop 1 (SL1), polyadenylation signal (polyA) and primer binding site (PBS), folded into independent structural motifs. In the monomeric RNA, SL1 was reconfigured into long- and short-range base pairings with polyA and PBS, respectively. We show that these interactions disrupt genome packaging, and additionally show that the PBS–SL1 interaction unexpectedly couples the PBS with dimerization and Pr55Gag binding. Altogether, our data provide insights into late stages of HIV-1 life cycle and a mechanistic explanation for the link between RNA dimerization and packaging.

To generate infectious viral particles, viruses must specifically select their genomic RNA from milieu that contains a complex mixture of cellular or non-genomic viral RNAs. In this review, we focus on the role of viral encoded RNA structures in genome packaging. We first discuss how packaging signals are constructed from local and long-range base pairings within viral genomes, as well as inter-molecular interactions between viral and host RNAs. Then, how genome packaging is regulated by the biophysical properties of RNA. Finally, we examine the impact of RNA packaging signals on viral evolution.

Genome-wide measurements of RNA structure can be obtained using reagents that react with unpaired bases, leading to adducts that can be identified by mutational profiling on next-generation sequencing machines. One drawback of these experiments is that short sequencing reads can rarely be mapped to specific transcript isoforms. Consequently, information is acquired as a population average in regions that are shared between transcripts, thus blurring the underlying structural landscape. Here, we present nanopore dimethylsulfate mutational profiling (Nano-DMS-MaP)—a method that exploits long-read sequencing to provide isoform-resolved structural information of highly similar RNA molecules. We demonstrate the value of Nano-DMS-MaP by resolving the complex structural landscape of human immunodeficiency virus-1 transcripts in infected cells. We show that unspliced and spliced transcripts have distinct structures at the packaging site within the common 5′ untranslated region, likely explaining why spliced viral RNAs are excluded from viral particles. Thus, Nano-DMS-MaP is a straightforward method to resolve biologically important transcript-specific RNA structures that were previously hidden in short-read ensemble analyses.