Biogenesis of canonical microRNAs (miRNAs) involves multiple steps: nuclear processing of primary miRNA (pri-miRNA) by DROSHA, nuclear export of precursor miRNA (pre-miRNA) by Exportin 5 (XPO5), and cytoplasmic processing of pre-miRNA by DICER. To gain a deeper understanding of the contribution of each of these maturation steps, we deleted DROSHA, XPO5, and DICER in the same human cell line, and analyzed their effects on miRNA biogenesis. Canonical miRNA production was completely abolished in DROSHA-deleted cells, whereas we detected a few DROSHA-independent miRNAs including three previously unidentified noncanonical miRNAs (miR-7706, miR-3615, and miR-1254). In contrast to DROSHA knockout, many canonical miRNAs were still detected without DICER albeit at markedly reduced levels. In the absence of DICER, pre-miRNAs are loaded directly onto AGO and trimmed at the 3′ end, yielding miRNAs from the 5′ strand (5p miRNAs). Interestingly, in XPO5 knockout cells, most miRNAs are affected only modestly, suggesting that XPO5 is necessary but not critical for miRNA maturation. Our study demonstrates an essential role of DROSHA and an important contribution of DICER in the canonical miRNA pathway, and reveals that the function of XPO5 can be complemented by alternative mechanisms. Thus, this study allows us to understand differential contributions of key biogenesis factors, and provides with valuable resources for miRNA research.icroRNA (miRNA) biogenesis begins with the synthesis of primary miRNA (pri-miRNA) by RNA polymerase II (1). The stem-loop structure embedded in pri-miRNA is cleaved by the Microprocessor complex composed of DROSHA and DGCR8 (2-6). The released hairpin, called precursor miRNA (pre-miRNA), is exported to the cytoplasm by Exportin 5 (XPO5) in a Ran-GTPdependent manner (7-9). In the cytoplasm, the pre-miRNA is further processed by DICER, producing a duplex RNA of ∼22 nt with its 3′ ends having a two nucleotide overhang (10-13). The duplex is loaded onto the ARGONAUTE (AGO) proteins, and one strand of the duplex remains as mature miRNA, whereas the other strand is discarded from AGO (11,14). The strand selection is dictated mainly by the relative thermodynamic stability of the two ends of the duplex: the strand whose 5′ terminal nucleotides are less stable is selected as mature miRNA (15,16). miRNAs originating from the 5′ and 3′ strands of pre-miRNA are referred to as the 5p and 3p miRNAs, respectively. Mammals have four closely related AGO proteins (AGO1-4) that interact with deadenylation factors and translational machinery to induce mRNA degradation and translational repression.Although the aforementioned canonical pathway accounts for the production of most miRNAs (1), it has also been shown that there exist alternative (noncanonical) pathways for miRNA biogenesis, which bypass a part of the biogenesis steps mentioned above. Mirtrons are one of the first miRNA groups described as noncanonical miRNAs, which do not require DROSHA for their production (17-19). Because mirtrons are located inside short ...

Although more than 100 types of RNA modification have been described thus far, most of them were thought to be rare in mRNAs and in regulatory noncoding RNAs. Recent developments have unveiled that at least some of the modifications are considerably abundant and widely conserved. This Minireview summarizes the molecular machineries and biological functions of methylation (N6-methyladenosine, m(6)A) and uridylation (U-tail).

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Terminal uridylyl transferases (TUTs) function as integral regulators of microRNA (miRNA) biogenesis. Using biochemistry, single-molecule, and deep sequencing techniques, we here investigate the mechanism by which human TUT7 (also known as ZCCHC6) recognizes and uridylates precursor miRNAs (pre-miRNAs) in the absence of Lin28. We find that the overhang of a pre-miRNA is the key structural element that is recognized by TUT7 and its paralogues, TUT4 (ZCCHC11) and TUT2 (GLD2/PAPD4). For group II pre-miRNAs, which have a 1-nt 3′ overhang, TUT7 restores the canonical end structure (2-nt 3′ overhang) through mono-uridylation, thereby promoting miRNA biogenesis. For pre-miRNAs where the 3′ end is further recessed into the stem (as in 3′ trimmed pre-miRNAs), TUT7 generates an oligo-U tail that leads to degradation. In contrast to Lin28-stimulated oligo-uridylation, which is processive, a distributive mode is employed by TUT7 for both mono- and oligo-uridylation in the absence of Lin28. The overhang length dictates the frequency (but not duration) of the TUT7-RNA interaction, thus explaining how TUT7 differentiates pre-miRNA species with different overhangs. Our study reveals dual roles and mechanisms of uridylation in repair and removal of defective pre-miRNAs.

Highlights d mir-451 is a Dicer-independent miRNA whose biogenesis requires its neighbor mir-144 d Both small loop and short stem render nuclear processing of mir-451 suboptimal d mir-451 processing involves local recruitment and transfer of Microprocessor d Genomic analyses show suboptimal canonical miRNAs preferentially reside in operons

Mammalian microRNAs (miRNAs) are highly stable in most cell types, and their decay mechanism remains largely unknown. Here we report that some miRNAs degrade rapidly upon the loss of cell adhesion. When cells are grown at low density or cells are detached by trypsinization or EGTA treatment, mature miR-141 is downregulated while miR-200c from a common primary transcript (pri-miR-200c∼141) remains unaffected. Blockade of transcription by Actinomycin D leads to rapid depletion of miR-141 with a half-life of <1 hr when cells are detached, indicating that the regulation occurs via RNA decay. A sequence motif (UGUCU) in the center of miR-141 is necessary for the regulation. We further find that many other miRNAs including miR-200a, miR-34a, miR-29b, miR-301a, and miR-21 are degraded upon cell splitting. Induced destruction of persistent regulatory molecules such as miRNAs may increase cellular plasticity and facilitate cellular remodeling in response to the changes in cell adhesion.

In this work, we used the health check-up data of more than 111,000 subjects for analysis, using only the data with all 35 variables entered. For the prediction of biological age, traditional statistical methods and four AI techniques (RF, XGB, SVR, and DNN), which are widely used recently, were simultaneously used to compare the predictive power. This study showed that AI models produced about 1.6 times stronger linear relationship on average than statistical models. In addition, the regression analysis on the predicted BA and CA revealed similar differences in terms of both the correlation coefficients (linear model: 0.831, polynomial model: 0.996, XGB model: 0.66, RF model: 0.927, SVR model: 0.787, DNN model: 0.998) and R2 values. Through this work, we confirmed that AI techniques such as the DNN model outperformed traditional statistical methods in predicting biological age.

In this paper, we reported that the levels of specific microRNAs (miRNAs) decrease when cells are grown at low density or when cells are detached from a culture dish. Based on our results, we proposed that some miRNAs are selectively destabilized depending on the adhesion status of the cells. However, in subsequent studies, we discovered that structured miRNAs with low GC content, such as miR-141, miR-29b, miR-21, miR-106b, miR-15a, and miR-34a, are selectively lost during sample preparation rather than degraded in the cell. The small RNA loss occurs when a small number of cells is used for RNA preparation using the standard TRIzol protocol (see in this issue for details). These findings provide an alternative explanation for our original data. While the original data are all reproducible, we are retracting the paper because we feel the main conclusions have been compromised. We apologize for any inconvenience this may have caused.