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PreprintCited by 133MicroRNA in disease regulationRNA Research and SplicingRNA Interference and Gene Delivery

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Global analyses of the dynamics of mammalian microRNA metabolism

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Kingston, Elena R., Bartel, David P.·2019·Genome Research
DOI 10.1101/607150PMC PMC6836734

Preprint — published as 10.1101/gr.251421.119 · Paper page

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Abstract

Rates of production and degradation together specify microRNA (miRNA) abundance and dynamics. Here, we used approach-to-equilibrium metabolic labeling to assess these rates for 176 miRNAs in contact-inhibited mouse embryonic fibroblasts (MEFs), 182 miRNAs in dividing MEFs, and 136 miRNAs in mouse embryonic stem cells (mESCs). MicroRNA duplexes, each comprising a mature miRNA and its passenger strand, are produced at rates as fast as 114 ± 49 copies/cell per min, which exceeds rates reported for any mRNAs. These duplexes are rapidly loaded into Argonaute, with <10 min typically required for duplex loading and silencing-complex maturation. Within Argonaute, guide strands have stabilities that vary by 100-fold. Half-lives also vary globally between cell lines, with median values ranging from 6.3 to 34 h in mESCs and contact-inhibited MEFs, respectively. Moreover, relative half-lives for individual miRNAs vary between cell types, implying the influence of cell-specific factors in dictating turnover rate. The apparent influence of miRNA regions most important for targeting, together with the effect of one target on miR-7a-5p accumulation, suggest that targets fulfill this role. Analysis of the tailing and trimming of miRNA 3′ termini showed that the flux was typically greatest through the isoform tailed with a single uridine, although changes in this flux did not correspond to changes in stability, which suggested that the processes of tailing and trimming might be independent from that of decay. Together these results establish a framework for describing the dynamics and regulation of miRNAs throughout their lifecycle.

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Figure 1. Labeling with 5EU generates reproducible miRNA half-life values. (A) Schematic of the experimental setup. 5EU is added at time zero, and samples are collected at subsequent time intervals. RNA is extracted from each sample, and a small fraction of this extracted RNA is used to generate small-RNA sequencing libraries. The remainder of the RNA is mixed with quantitative standards (stds.), and molecules with one or more 5EU nucleotides are biotinylated and captured using streptavidin beads. RNA eluted from the beads is prepared for small-RNA sequencing. (B) Equations used for fitting approach-to-steady-state data. Equation 1 represents the single-exponential model used to fit a single decay rate for guide strands. Equation 2 represents the biexponential model used to fit two decay rates for both passenger and guide strands when assessing passenger-strand half-lives. Fits returned estimates for α (production rate), βn (degradation rate, with n distinguishing the two rates of Equation 2), f (fraction of molecules exhibiting the corresponding degradation rate), and t0 (time offset). The variable g describes the rate of cell doubling and was set manually based on experimental observations. Fits were carried out for each miRNA guide or passenger strand that satisfied an expression cut-off of 60 reads per million miRNA-mapping reads (i.e., 60 RPM) at each time point. (C) Representative fits to data from contact-inhibited MEFs. Data are plotted with black points, and single-exponential fits with a red line. Time courses representing the 10th through 90th deciles in goodness-of-fit are shown in order of increasing goodness-of-fit (from top left to bottom right). (D) Reproducibility of half-life measurements for guide strands. Shown is the relationship between values determined independently from each of the two biological replicates from contact-inhibited MEFs.
Figure 1. Labeling with 5EU generates reproducible miRNA half-life values. (A) Schematic of the experimental setup. 5EU is added at time zero, and samples are collected at subsequent time intervals. RNA is extracted from each sample, and a small fraction of this extracted RNA is used to generate small-RNA sequencing libraries. The remainder of the RNA is mixed with quantitative standards (stds.), and molecules with one or more 5EU nucleotides are biotinylated and captured using streptavidin beads. RNA eluted from the beads is prepared for small-RNA sequencing. (B) Equations used for fitting approach-to-steady-state data. Equation 1 represents the single-exponential model used to fit a single decay rate for guide strands. Equation 2 represents the biexponential model used to fit two decay rates for both passenger and guide strands when assessing passenger-strand half-lives. Fits returned estimates for α (production rate), βn (degradation rate, with n distinguishing the two rates of Equation 2), f (fraction of molecules exhibiting the corresponding degradation rate), and t0 (time offset). The variable g describes the rate of cell doubling and was set manually based on experimental observations. Fits were carried out for each miRNA guide or passenger strand that satisfied an expression cut-off of 60 reads per million miRNA-mapping reads (i.e., 60 RPM) at each time point. (C) Representative fits to data from contact-inhibited MEFs. Data are plotted with black points, and single-exponential fits with a red line. Time courses representing the 10th through 90th deciles in goodness-of-fit are shown in order of increasing goodness-of-fit (from top left to bottom right). (D) Reproducibility of half-life measurements for guide strands. Shown is the relationship between values determined independently from each of the two biological replicates from contact-inhibited MEFs.CC BY-NC · PubMed Central
Figure 2. Dynamics of miRNA guide strands in contact-inhibited MEFs. (A) Distribution of production rates for guide strands in contact-inhibited MEFs. (B) Distribution of half-life values for guide strands in contact-inhibited MEFs. (C) Relationship between steady-state abundance (reads in the 1-wk input sample) and production rate of guide strands in contact-inhibited MEFs. Outliers that passed an expression threshold (production rate >5 copies/h/cell) and differed significantly from the best linear fit (|z-score| > 2) are labeled. (D) Relationship between steady-state abundance (reads in the 1-wk input sample) and half-life of guide strands in contact-inhibited MEFs. The eight most rapidly turned over miRNAs, in order from least to most stable, were miR-7a-5p, miR-154-3p, miR-328-3p, miR-503-5p, miR-450b-5p, miR-329-5p, miR-495-3p, and miR-376b-3p.
Figure 2. Dynamics of miRNA guide strands in contact-inhibited MEFs. (A) Distribution of production rates for guide strands in contact-inhibited MEFs. (B) Distribution of half-life values for guide strands in contact-inhibited MEFs. (C) Relationship between steady-state abundance (reads in the 1-wk input sample) and production rate of guide strands in contact-inhibited MEFs. Outliers that passed an expression threshold (production rate >5 copies/h/cell) and differed significantly from the best linear fit (|z-score| > 2) are labeled. (D) Relationship between steady-state abundance (reads in the 1-wk input sample) and half-life of guide strands in contact-inhibited MEFs. The eight most rapidly turned over miRNAs, in order from least to most stable, were miR-7a-5p, miR-154-3p, miR-328-3p, miR-503-5p, miR-450b-5p, miR-329-5p, miR-495-3p, and miR-376b-3p.CC BY-NC · PubMed Central
Figure 3. Dynamics of passenger strands in contact-inhibited MEFs. (A) Examples of fits for passenger strands and corresponding guide strands (left and right, respectively). Single- and biexponential fits are indicated (red and blue lines, respectively) with corresponding R2 values. (B) Half-life distributions for guide and passenger strands (orange and teal, respectively) obtained using either the single-exponential (single exp.) or biexponential (biexp.) fitting methods (box, quartiles; whiskers, at most 1.5 times the inter-quartile range). The major half-life was the one that corresponded to the majority of the specified strand (i.e., for the passenger strand, the molecules not incorporated into the mature silencing complex, and for the guide strand, the molecules incorporated into the mature complex), whereas the minor half-life was the one that corresponded to the minority of the specified strand. P values (two-sample t-test) are shown for the indicated comparisons.
Figure 3. Dynamics of passenger strands in contact-inhibited MEFs. (A) Examples of fits for passenger strands and corresponding guide strands (left and right, respectively). Single- and biexponential fits are indicated (red and blue lines, respectively) with corresponding R2 values. (B) Half-life distributions for guide and passenger strands (orange and teal, respectively) obtained using either the single-exponential (single exp.) or biexponential (biexp.) fitting methods (box, quartiles; whiskers, at most 1.5 times the inter-quartile range). The major half-life was the one that corresponded to the majority of the specified strand (i.e., for the passenger strand, the molecules not incorporated into the mature silencing complex, and for the guide strand, the molecules incorporated into the mature complex), whereas the minor half-life was the one that corresponded to the minority of the specified strand. P values (two-sample t-test) are shown for the indicated comparisons.CC BY-NC · PubMed Central
Figure 4. Features associated with rapid miRNA turnover. (A) Differences in half-life for pairs of family members or randomly paired guides. For each pair-wise comparison of all members within each miRNA family, half-life percent differences were computed as the absolute value of the difference between half-lives, divided by the mean of the two half-lives, with this fraction then multiplied by 100. The log2-transformed percent-difference values of all such comparisons in contact-inhibited MEFs are plotted (box, quartiles; whiskers, at most 1.5 times the inter-quartile range). Twenty-five equally sized cohorts of randomly paired guides were analyzed in the same way, with the cohort shown for comparison being the one with the median value of significance (P value, two-sample t-test). (B) Relationship between half-life difference and the number of nonidentical nucleotides (Hamming distance) when comparing pairs of family members. Only nucleotides 3′ of the seed region were considered for the Hamming-distance measurement. Greater Hamming distances represent more dissimilar sequences. Significance of the correlation was determined by a t-test. (C) The effect of Cyrano on steady-state miR-7 levels in contact-inhibited MEFs. Shown is a scan of a northern blot analyzing RNA from wild-type and Cyrano-knockout contact-inhibited MEFs. For each cell line, four biological replicates were analyzed, sequentially probing for miR-17, which served as a loading control, and then for miR-7. The fold-difference in miR-7 relative to the average miR-7 level in wild-type MEFs is shown below each lane.
Figure 4. Features associated with rapid miRNA turnover. (A) Differences in half-life for pairs of family members or randomly paired guides. For each pair-wise comparison of all members within each miRNA family, half-life percent differences were computed as the absolute value of the difference between half-lives, divided by the mean of the two half-lives, with this fraction then multiplied by 100. The log2-transformed percent-difference values of all such comparisons in contact-inhibited MEFs are plotted (box, quartiles; whiskers, at most 1.5 times the inter-quartile range). Twenty-five equally sized cohorts of randomly paired guides were analyzed in the same way, with the cohort shown for comparison being the one with the median value of significance (P value, two-sample t-test). (B) Relationship between half-life difference and the number of nonidentical nucleotides (Hamming distance) when comparing pairs of family members. Only nucleotides 3′ of the seed region were considered for the Hamming-distance measurement. Greater Hamming distances represent more dissimilar sequences. Significance of the correlation was determined by a t-test. (C) The effect of Cyrano on steady-state miR-7 levels in contact-inhibited MEFs. Shown is a scan of a northern blot analyzing RNA from wild-type and Cyrano-knockout contact-inhibited MEFs. For each cell line, four biological replicates were analyzed, sequentially probing for miR-17, which served as a loading control, and then for miR-7. The fold-difference in miR-7 relative to the average miR-7 level in wild-type MEFs is shown below each lane.CC BY-NC · PubMed Central
Figure 5. Dynamics of miRNA guide strands in dividing MEFs and mESCs. (A,B) Half-life distributions for guide strands in dividing MEFs (A) and mESCs (B). Half-lives were capped at the duration of the longest time interval (72 h and 24 h in dividing MEFs and mESCs, respectively), as modeling indicated that longer half-lives would be fit less accurately. (C,D) Guide-strand half-lives in dividing MEFs (C) and mESCs (D) as a function of those half-lives in contact-inhibited MEFs. (E,F) Relationship between steady-state abundance and half-life in dividing MEFs (E) and mESCs (F). Steady-state abundance is measured as reads in the 72- and 24-h input sample, respectively.
Figure 5. Dynamics of miRNA guide strands in dividing MEFs and mESCs. (A,B) Half-life distributions for guide strands in dividing MEFs (A) and mESCs (B). Half-lives were capped at the duration of the longest time interval (72 h and 24 h in dividing MEFs and mESCs, respectively), as modeling indicated that longer half-lives would be fit less accurately. (C,D) Guide-strand half-lives in dividing MEFs (C) and mESCs (D) as a function of those half-lives in contact-inhibited MEFs. (E,F) Relationship between steady-state abundance and half-life in dividing MEFs (E) and mESCs (F). Steady-state abundance is measured as reads in the 72- and 24-h input sample, respectively.CC BY-NC · PubMed Central
Figure 6. Dynamics of 3′-end isoforms. (A) Isoform accumulation for miR-23a-3p and miR-674-5p, two guide RNAs for which accumulation of derivatives of the initial isoform overtook that of the initial isoform. (Top) Absolute accumulation of the initial isoform (black) and its major derivatives, in which it is either trimmed by 1 nt (−1, blue) or tailed with either a single A (+1[A], red) or a single U (+1[U], green). Lines connect the mean values for each time point and do not represent fits to the data. (Bottom) Fractional abundance of the initial isoform and its major derivatives. (B) Schematic depicting the isoform-conversion model that was fit to the data and used for simulations. Arrows represent processes catalyzed by the cellular milieu of nucleotidyl transferases, phosphodiesterases, and other enzymes; the model is agnostic to the particular enzyme that carries out each reaction. Rate constants extracted from the fit are labeled (kn). Isoform nomenclature is as in A. (C,D) Representative examples of fits to isoform dynamics for miRNAs in contact-inhibited MEFs. Shown is the plot from the middle of the lowest quartile (miR-145a-5p, R2 = 0.92) and the plot from the middle of the highest quartile (miR-322-5p, R2 = 0.96) of goodness-of-fit (R2), when fitting data from both replicates. (E) Relative rates of conversion to the +1(A), +1(U), and −1 isoforms in contact-inhibited MEFs. Rate constants of conversion to each isoform (k3, k4, and k5 for +1(A), +1(U), and −1, respectively) were normalized to the summed conversion rate constant (k3 + k4 + k5) to generate the relative rates of conversion. Simulations indicated that conversion rate constants >1 h−1 could not be accurately fit, and thus conversion rate constants were capped at this value. Significance was evaluated with a Mann–Whitney U test, and P values are shown. (F) Rate constants for disappearance (k6 + k9, k7 + k10, or k8 + k11) of the +1(A), +1(U), and −1 isoforms, respectively, in contact-inhibited MEFs. Simulations indicated that disappearance rate constants >10 h−1 could not be accurately fit, and thus disappearance rate constants were capped at this value. Significance was evaluated with a Mann–Whitney U test, and all significant comparisons are indicated together with their P values. (G) Correlation between half-life ratios (dividing values from dividing MEFs by those from contact-inhibited MEFs) and ratios of the flux through the +1(U) isoform (again dividing values from dividing MEFs by those from contact-inhibited MEFs). Dividing MEFs are denoted as dMEFs; contact-inhibited MEFs are denoted as ciMEFs.
Figure 6. Dynamics of 3′-end isoforms. (A) Isoform accumulation for miR-23a-3p and miR-674-5p, two guide RNAs for which accumulation of derivatives of the initial isoform overtook that of the initial isoform. (Top) Absolute accumulation of the initial isoform (black) and its major derivatives, in which it is either trimmed by 1 nt (−1, blue) or tailed with either a single A (+1[A], red) or a single U (+1[U], green). Lines connect the mean values for each time point and do not represent fits to the data. (Bottom) Fractional abundance of the initial isoform and its major derivatives. (B) Schematic depicting the isoform-conversion model that was fit to the data and used for simulations. Arrows represent processes catalyzed by the cellular milieu of nucleotidyl transferases, phosphodiesterases, and other enzymes; the model is agnostic to the particular enzyme that carries out each reaction. Rate constants extracted from the fit are labeled (kn). Isoform nomenclature is as in A. (C,D) Representative examples of fits to isoform dynamics for miRNAs in contact-inhibited MEFs. Shown is the plot from the middle of the lowest quartile (miR-145a-5p, R2 = 0.92) and the plot from the middle of the highest quartile (miR-322-5p, R2 = 0.96) of goodness-of-fit (R2), when fitting data from both replicates. (E) Relative rates of conversion to the +1(A), +1(U), and −1 isoforms in contact-inhibited MEFs. Rate constants of conversion to each isoform (k3, k4, and k5 for +1(A), +1(U), and −1, respectively) were normalized to the summed conversion rate constant (k3 + k4 + k5) to generate the relative rates of conversion. Simulations indicated that conversion rate constants >1 h−1 could not be accurately fit, and thus conversion rate constants were capped at this value. Significance was evaluated with a Mann–Whitney U test, and P values are shown. (F) Rate constants for disappearance (k6 + k9, k7 + k10, or k8 + k11) of the +1(A), +1(U), and −1 isoforms, respectively, in contact-inhibited MEFs. Simulations indicated that disappearance rate constants >10 h−1 could not be accurately fit, and thus disappearance rate constants were capped at this value. Significance was evaluated with a Mann–Whitney U test, and all significant comparisons are indicated together with their P values. (G) Correlation between half-life ratios (dividing values from dividing MEFs by those from contact-inhibited MEFs) and ratios of the flux through the +1(U) isoform (again dividing values from dividing MEFs by those from contact-inhibited MEFs). Dividing MEFs are denoted as dMEFs; contact-inhibited MEFs are denoted as ciMEFs.CC BY-NC · PubMed Central

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Metadata

Authors
Kingston, E. R., & Bartel, D. P.
Affiliations
Howard Hughes Medical Institute (US)
Corresponding author
Bartel, David P.
ORCID
Venue
Genome Research
Publisher
openRxiv
Published
2019-04-12
Volume
29
Issue
11
Pages
1777-1790
ISSN
1088-9051 (ISSN-L)
DOI
10.1101/607150
PMC
PMC6836734
OpenAlex
W2972836719
Cited by
133
References
1
Citations by year
2026: 19 · 2025: 15 · 2024: 21 · 2023: 27 · 2022: 19 · 2021: 18 · 2020: 10 · 2019: 4
Type
posted content
Language
en
Open access
Locations
  • Genome Research (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
  • HighWire Press Open Archive (submittedVersion)
Funders
  • National Science Foundation
  • Howard Hughes Medical Institute
  • National Institutes of Health
  • National Institute of General Medical Sciences (R35GM118135)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Interference and Gene Delivery
Keywords
microRNA biogenesis, miRNA stability, Argonaute proteins, microRNA target regulation, miR-7, mouse embryonic fibroblasts, mouse embryonic stem cells, cell cycle
MeSH terms
Animals, Cells, Cultured, MicroRNAs, Mice, High-Throughput Screening Assays

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