MicroRNAs (miRNAs) are small regulatory RNAs processed from stem-loop regions of primary transcripts (pri-miRNAs), with the choice of stem loops for initial processing largely determining what becomes a miRNA. To identify sequence and structural features influencing this choice, we determined cleavage efficiencies of >50,000 variants of three human pri-miRNAs, focusing on the regions intractable to previous high-throughput analyses. Our analyses revealed a mismatched motif in the basal stem region, a preference for maintaining or improving base pairing throughout the remainder of the stem, and a narrow stem-length preference of 35 ± 1 base pairs. Incorporating these features with previously identified features, including three primary-sequence motifs, yielded a unifying model defining mammalian pri-miRNAs in which motifs help orient processing and increase efficiency, with the presence of more motifs compensating for structural defects. This model enables generation of artificial pri-miRNAs, designed de novo, without reference to any natural sequence yet processed more efficiently than natural pri-miRNAs.

The Menu of Features that Define Primary MicroRNAs and Enable De Novo Design of MicroRNA Genes

A quantitative map of human primary microRNA processing sites

Micro-RNAs (miRNAs) are a class of non-coding RNAs (ncRNAs) that act as post-transcriptional regulators of gene expression. Since their discovery in 1993, they have been the subject of deep study due to their involvement in many important biological processes. Compared with other ncRNAs, miRNAs are generated from devoted transcriptional units which are processed by a specific set of endonucleases. The contribution of structural biology methods for understanding miRNA biogenesis and function has been essential for the dissection of their roles in cell biology and human disease. In this review, we summarize the application of structural biology for the characterization of the molecular players involved in miRNA biogenesis (processors and effectors), starting from the X-ray crystallography methods to the more recent cryo-electron microscopy protocols.

https://www.mdpi.com/2311-553X/8/1/10/pdf?version=1642494077

A Structural View of miRNA Biogenesis and Function

Most microRNAs (miRNAs) are processed by two ribonuclease III enzymes. The first cleavage is performed by Microprocessor that is composed of RNase III enzyme Drosha and DGCR8, and the second by another RNase III enzyme Dicer. There are many examples of miRNAs that are poor substrates for Drosha and Dicer, owing to their suboptimal structures. However, a number of these suboptimal miRNAs are known to be expressed at the same or higher level as their neighboring structurally-optimal miRNAs. Recent studies suggest that the clustered orientation of these suboptimal miRNAs is the explanation for this phenomenon. It has been observed that the biogenesis of these suboptimal miRNAs can be affected by the expression of their neighboring optimal miRNAs. This principle is expected to apply more broadly, as it has been shown that a large percentage of suboptimal miRNAs reside within operons.

/pdf/microrna-clustering-on-the-biogenesis-of-suboptimal-2kibbzrcyw.pdf

MicroRNA clustering on the biogenesis of suboptimal microRNAs

MicroRNAs (miRNAs) are small regulatory RNAs involved in virtually all biological processes. Although a large number of them are co-expressed from clusters, little is known regarding the impact of this organization on the regulation of their accumulation. In this study, we set to decipher the regulatory mechanism controlling the expression of the ten clustered pre-miRNAs from Kaposis sarcoma associated herpesvirus (KSHV). We measured in vitro the efficiency of cleavage of each individual pre-miRNA by the Microprocessor. Strikingly, pre-miR-K1 and -K3 were the most efficiently cleaved pre-miRNAs but their mature forms accumulated at low levels, indicating that they might perform an additional function. A mutational analysis showed that they are indeed important for the optimal expression of the whole set of miRNAs. We showed that this solely relies on the presence of a canonical pre-miRNA at this localization since we could functionally replace pre-miR-K1 by a heterologous pre-miRNA. Further in vitro processing analysis suggests that the two stem-loops act in cis and that the cluster is cleaved in a sequential manner. Finally, we showed that we can exploit this feature of the cluster to inhibit the expression of the whole set of miRNAs by targeting the pre-miR-K1 with LNA-based antisense oligonucleotides.

/pdf/cis-regulation-within-a-cluster-of-viral-micrornas-336b5tql40.pdf

Cis regulation within a cluster of viral microRNAs

The microprocessor complex cleaves the primary transcript of microRNA (pri-miRNA) to initiate miRNA maturation. Microprocessor is known to consist of RNase III DROSHA and dsRNA-binding DGCR8. Here, we identify Enhancer of Rudimentary Homolog (ERH) as a new component of Microprocessor. Through a crystal structure and biochemical experiments, we reveal that ERH uses its hydrophobic groove to bind to a conserved region in the N-terminus of DGCR8, in a 2:2 stoichiometry. Knock-down of ERH or deletion of the DGCR8 N-terminus results in a reduced processing of suboptimal pri-miRNAs in polycistronic miRNA clusters. ERH increases the processing of suboptimal pri-miR-451 in a manner dependent on its neighboring pri-miR-144. Thus, the ERH dimer may mediate 'cluster assistance' in which Microprocessor is loaded onto a poor substrate with help from a high-affinity substrate in the same cluster. Our study reveals a role of ERH in the miRNA biogenesis pathway.

ERH facilitates microRNA maturation through the interaction with the N-terminus of DGCR8.

The RNA recognition motif (RRM) binds to nucleic acids as well as proteins. More than one such domain is found in the pre-mRNA processing hnRNP proteins. While the mode of RNA recognition by RRMs is known, the molecular basis of their protein interaction remains obscure. Here we describe the mode of interaction between hnRNP L and LL with the methyltransferase SETD2. We demonstrate that for the interaction to occur, a leucine pair within a highly conserved stretch of SETD2 insert their side chains in hydrophobic pockets formed by hnRNP L RRM2. Notably, the structure also highlights that RRM2 can form a ternary complex with SETD2 and RNA. Remarkably, mutating the leucine pair in SETD2 also results in its reduced interaction with other hnRNPs. Importantly, the similarity that the mode of SETD2-hnRNP L interaction shares with other related protein-protein interactions reveals a conserved design by which splicing regulators interact with one another.

Structural basis of the interaction between SETD2 methyltransferase and hnRNP L paralogs for governing co-transcriptional splicing.

https://biorxiv.org/content/10.1101/2021.05.22.445248v1.full.pdf

Siyuan Shen

Papers

ERH facilitates microRNA maturation through the interaction with the N-terminus of DGCR8.

Structural basis of the interaction between SETD2 methyltransferase and hnRNP L paralogs for governing co-transcriptional splicing.

Structural basis of the interaction between SETD2 methyltransferase and hnRNP L paralogs for governing co-transcriptional splicing