A mouse model with high clonal barcode diversity for joint lineage, transcriptomic, and epigenomic profiling in single cells.

Cellular lineage histories and their molecular states encode fundamental principles of tissue development and homeostasis. Current lineage-recording mouse models have insufficient barcode diversity and single-cell lineage coverage for profiling tissues composed of millions of cells. Here, we developed DARLIN, an inducible Cas9 barcoding mouse line that utilizes terminal deoxynucleotidyl transferase (TdT) and 30 CRISPR target sites. DARLIN is inducible, generates massive lineage barcodes across tissues, and enables the detection of edited barcodes in ∼70% of profiled single cells. Using DARLIN, we examined fate bias within developing hematopoietic stem cells (HSCs) and revealed unique features of HSC migration. Additionally, we established a protocol for joint transcriptomic and epigenomic single-cell measurements with DARLIN and found that cellular clonal memory is associated with genome-wide DNA methylation rather than gene expression or chromatin accessibility. DARLIN will enable the high-resolution study of lineage relationships and their molecular signatures in diverse tissues and physiological contexts.

MicroRNA 3'-compensatory pairing occurs through two binding modes, with affinity shaped by nucleotide identity and position.

MicroRNAs (miRNAs), in association with Argonaute (AGO) proteins, direct repression by pairing to sites within mRNAs. Compared to pairing preferences of the miRNA seed region (nucleotides 2-8), preferences of the miRNA 3' region are poorly understood, due to the sparsity of measured affinities for the many pairing possibilities. We used RNA bind-n-seq with purified AGO2-miRNA complexes to measure relative affinities of >1000 3'-pairing architectures for each miRNA. In some cases, optimal 3' pairing increased affinity by >500 fold. Some miRNAs had two high-affinity 3'-pairing modes-one of which included additional nucleotides bridging seed and 3' pairing to enable high-affinity pairing to miRNA nucleotide 11. The affinity of binding and the position of optimal pairing both tracked with the occurrence of G or oligo(G/C) nucleotides within the miRNA. These and other results advance understanding of miRNA targeting, providing insight into how optimal 3' pairing is determined for each miRNA.

Noncoding RNAs: biology and applications-a Keystone Symposia report.

The human transcriptome contains many types of noncoding RNAs, which rival the number of protein-coding species. From long noncoding RNAs (lncRNAs) that are over 200 nucleotides long to piwi-interacting RNAs (piRNAs) of only 20 nucleotides, noncoding RNAs play important roles in regulating transcription, epigenetic modifications, translation, and cell signaling. Roles for noncoding RNAs in disease mechanisms are also being uncovered, and several species have been identified as potential drug targets. On May 11-14, 2021, the Keystone eSymposium "Noncoding RNAs: Biology and Applications" brought together researchers working in RNA biology, structure, and technologies to accelerate both the understanding of RNA basic biology and the translation of those findings into clinical applications.

The Dynamics of Cytoplasmic mRNA Metabolism.

For all but a few mRNAs, the dynamics of metabolism are unknown. Here, we developed an experimental and analytical framework for examining these dynamics for mRNAs from thousands of genes. mRNAs of mouse fibroblasts exit the nucleus with diverse intragenic and intergenic poly(A)-tail lengths. Once in the cytoplasm, they have a broad (1000-fold) range of deadenylation rate constants, which correspond to cytoplasmic lifetimes. Indeed, with few exceptions, degradation appears to occur primarily through deadenylation-linked mechanisms, with little contribution from either endonucleolytic cleavage or deadenylation-independent decapping. Most mRNA molecules degrade only after their tail lengths fall below 25 nt. Decay rate constants of short-tailed mRNAs vary broadly (1000-fold) and are larger for short-tailed mRNAs that have previously undergone more rapid deadenylation. This coupling helps clear rapidly deadenylated mRNAs, enabling the large range in deadenylation rate constants to impart a similarly large range in stabilities.

The biochemical basis of microRNA targeting efficacy.

MicroRNAs (miRNAs) act within Argonaute proteins to guide repression of messenger RNA targets. Although various approaches have provided insight into target recognition, the sparsity of miRNA-target affinity measurements has limited understanding and prediction of targeting efficacy. Here, we adapted RNA bind-n-seq to enable measurement of relative binding affinities between Argonaute-miRNA complexes and all sequences ≤12 nucleotides in length. This approach revealed noncanonical target sites specific to each miRNA, miRNA-specific differences in canonical target-site affinities, and a 100-fold impact of dinucleotides flanking each site. These data enabled construction of a biochemical model of miRNA-mediated repression, which was extended to all miRNA sequences using a convolutional neural network. This model substantially improved prediction of cellular repression, thereby providing a biochemical basis for quantitatively integrating miRNAs into gene-regulatory networks.

Impact of MicroRNA Levels, Target-Site Complementarity, and Cooperativity on Competing Endogenous RNA-Regulated Gene Expression.

Expression changes of competing endogenous RNAs (ceRNAs) have been proposed to influence microRNA (miRNA) activity and thereby regulate other transcripts containing miRNA-binding sites. Here, we find that although miRNA levels define the extent of repression, they have little effect on the magnitude of the ceRNA expression change required to observe derepression. Canonical 6-nt sites, which typically mediate modest repression, can nonetheless compete for miRNA binding, with potency ∼20% of that observed for canonical 8-nt sites. In aggregate, low-affinity/background sites also contribute to competition. Sites with extensive additional complementarity can appear as more potent, but only because they induce miRNA degradation. Cooperative binding of proximal sites for the same or different miRNAs does increase potency. These results provide quantitative insights into the stoichiometric relationship between miRNAs and target abundance, target-site spacing, and affinity requirements for ceRNA-mediated gene regulation, and the unusual circumstances in which ceRNA-mediated gene regulation might be observed.

mRNA destabilization is the dominant effect of mammalian microRNAs by the time substantial repression ensues.

MicroRNAs (miRNAs) regulate target mRNAs through a combination of translational repression and mRNA destabilization, with mRNA destabilization dominating at steady state in the few contexts examined globally. Here, we extend the global steady-state measurements to additional mammalian contexts and find that regardless of the miRNA, cell type, growth condition, or translational state, mRNA destabilization explains most (66%->90%) miRNA-mediated repression. We also determine the relative dynamics of translational repression and mRNA destabilization for endogenous mRNAs as a miRNA is induced. Although translational repression occurs rapidly, its effect is relatively weak, such that by the time consequential repression ensues, the effect of mRNA destabilization dominates. These results imply that consequential miRNA-mediated repression is largely irreversible and provide other insights into the nature of miRNA-mediated regulation. They also simplify future studies, dramatically extending the known contexts and time points for which monitoring mRNA changes captures most of the direct miRNA effects.

Multicolor microRNA FISH effectively differentiates tumor types.

MicroRNAs (miRNAs) are excellent tumor biomarkers because of their cell-type specificity and abundance. However, many miRNA detection methods, such as real-time PCR, obliterate valuable visuospatial information in tissue samples. To enable miRNA visualization in formalin-fixed paraffin-embedded (FFPE) tissues, we developed multicolor miRNA FISH. As a proof of concept, we used this method to differentiate two skin tumors, basal cell carcinoma (BCC) and Merkel cell carcinoma (MCC), with overlapping histologic features but distinct cellular origins. Using sequencing-based miRNA profiling and discriminant analysis, we identified the tumor-specific miRNAs miR-205 and miR-375 in BCC and MCC, respectively. We addressed three major shortcomings in miRNA FISH, identifying optimal conditions for miRNA fixation and ribosomal RNA (rRNA) retention using model compounds and high-pressure liquid chromatography (HPLC) analyses, enhancing signal amplification and detection by increasing probe-hapten linker lengths, and improving probe specificity using shortened probes with minimal rRNA sequence complementarity. We validated our method on 4 BCC and 12 MCC tumors. Amplified miR-205 and miR-375 signals were normalized against directly detectable reference rRNA signals. Tumors were classified using predefined cutoff values, and all were correctly identified in blinded analysis. Our study establishes a reliable miRNA FISH technique for parallel visualization of differentially expressed miRNAs in FFPE tumor tissues.

Beyond secondary structure: primary-sequence determinants license pri-miRNA hairpins for processing.

To use microRNAs to downregulate mRNA targets, cells must first process these ~22 nt RNAs from primary transcripts (pri-miRNAs). These transcripts form RNA hairpins important for processing, but additional determinants must distinguish pri-miRNAs from the many other hairpin-containing transcripts expressed in each cell. Illustrating the complexity of this recognition, we show that most Caenorhabditis elegans pri-miRNAs lack determinants required for processing in human cells. To find these determinants, we generated many variants of four human pri-miRNAs, sequenced millions that retained function, and compared them with the starting variants. Our results confirmed the importance of pairing in the stem and revealed three primary-sequence determinants, including an SRp20-binding motif (CNNC) found downstream of most pri-miRNA hairpins in bilaterian animals, but not in nematodes. Adding this and other determinants to C. elegans pri-miRNAs imparted efficient processing in human cells, thereby confirming the importance of primary-sequence determinants for distinguishing pri-miRNAs from other hairpin-containing transcripts.