# Biochemical principles of miRNA targeting in flies

Joel Vega-Badillo, Phillip D Zamore, Karina Jouravleva

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Joel Vega-Badillo, Phillip D Zamore, Karina Jouravleva. Biochemical principles of miRNA targeting in flies. 2025. hal-04872426

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Distributed under a Creative Commons Attribution 4.0 International License
Biochemical principles of miRNA targeting in flies

Joel Vega-Badillo<fnref n="1" />, Phillip D. Zamore<fnref n="1" />,<fnref n="2" />,<fnref n="4" />,†, and Karina Jouravleva<fnref n="3" />,†

<footnote n="1">¹RNA Therapeutics Institute, University of Massachusetts Chan Medical School, 368 Plantation Street, Worcester, MA 01605, USA</footnote>

<footnote n="2">²Howard Hughes Medical Institute, University of Massachusetts Chan Medical School, 368 Plantation Street, Worcester, MA 01605, USA</footnote>

<footnote n="3">³Laboratoire de Biologie et Modélisation de la Cellule, École Normale Supérieure de Lyon, CNRS UMR5239, Inserm U1293, Université Claude Bernard Lyon 1, Lyon, France</footnote>

<footnote n="4">⁴Lead Contact</footnote>

<footnote>†For correspondence: karina.jouravleva@ens-lyon.fr (K.J.), phillip.zamore@umassmed.edu (P.D.Z.)</footnote>
## Summary

MicroRNAs-direct Argonaute proteins to repress complementary target mRNAs via mRNA degradation or translational inhibition. While mammalian miRNA targeting has been well studied, the principles by which *Drosophila* miRNAs bind their target RNAs remain to be fully characterized. Here, we use RNA Bind-n-Seq to systematically identify binding sites and measure their affinities for four highly expressed *Drosophila* miRNAs. Our results reveal a narrower range of binding site diversity in flies compared to mammals, with fly miRNAs favoring canonical seed-matched sites and exhibiting limited tolerance for imperfections within these sites. We also identified non-canonical site types, including nucleation-bulged and 3'-only sites, whose binding affinities are comparable to canonical sites. These findings establish a foundation for future computational models of *Drosophila* miRNA targeting, enabling predictions of regulatory outcomes in response to cellular signals, and advancing our understanding of miRNA-mediated regulation in flies.

## Keywords

miRNA, Argonaute, RISC, RNA interference, binding affinity, *Drosophila*
Introduction

In plants and animals, ~22-nt-long microRNAs (miRNAs) guide AGO-clade Argonaute proteins to repress partially complementary mRNA targets by accelerating their degradation¹⁻³ or inhibiting their translation⁴⁻⁷. Many loss-of-function miRNA mutants display developmental, physiological, and behavioral defects⁸,⁹.

In animals, the miRNA seed (miRNA nucleotide positions g2–g7) is the primary determinant for targeting, and pairing to the miRNA seed often suffices for target binding and repression⁶,¹⁰⁻¹⁴. Additional pairing to the miRNA 3' end (centered around g13–g16) can reinforce recognition of seed-matched targets and compensate for weak or imperfect seed pairing¹⁴⁻¹⁸. However, such 3'-supplementary or compensatory sites appear to be rare¹⁴,¹⁹,²⁰. Mammalian miRNA binding tolerates single wobble, bulged or mismatched nucleotides at specific positions within the seed²¹⁻²³. Adding to this complexity, some miRNAs bind “seedless” sites bearing extensive complementarity to the miRNA center (‘central sites’) or 3' nucleotides (‘3'-only sites’) with affinities comparable to canonical seed-matched sites²²⁻²⁴.

Partial complementarity of miRNA targets, non-canonical binding modes, local sequence-dependent interactions, and the generally modest repression of targets make prediction of animal miRNA regulatory targets difficult, despite two decades of research²²,²⁵. The most successful computational approaches typically predict miRNA binding rather than biologically important regulation⁹,²²,²⁵. In contrast to the large number of targets uncovered by cell culture or computational experiments¹⁶,¹⁹,²⁰,²⁶,²⁷, genetic experiments in *Caenorhabditis elegans*, *Drosophila melanogaster*, and mice suggest that miRNAs can act as ‘master regulators’ of specific biological processes, with repression of as few as a single mRNA explaining the primary function of the miRNA. In *Caenorhabditis elegans*, *lin-4* represses *lin-14* and is essential for transition between larval stages²⁸. In *Drosophila melanogaster*, *bantam* represses the pro-
apoptotic gene *head involution defective* (*hid*) regulating tissue growth in post-embryonic development<sup>29,30</sup>. In circadian cells, *bantam* silences a core circadian clock gene (*clock*) affecting circadian timekeeping<sup>31</sup>. Transgenic flies expressing *clock* without 3' UTR *bantam* sites are arrhythmic; introduction of a wild-type copy of *clock* rescues this rhythm defect. In mice, miR-9 represses the orphan nuclear receptor tailless homologue (TLX) and induces neuronal differentiation<sup>32</sup>. Neural stem cells expressing TLX lacking miR-9 binding sites recover proliferative capacity and are not able to differentiate into astrocytes.

Much of our understanding of miRNA targeting derives from high-throughput biochemical analyses of human and mouse miRNAs<sup>21-33</sup>, and these insights have improved miRNA target prediction<sup>22</sup>. Here, we use RNA Bind-n-Seq (RBNS) to identify binding sites and obtain high-throughput affinity measurements for four abundant *Drosophila* miRNAs loaded into Ago1. Analyses of these data reveal that fly miRNAs bind a more restricted number of site types compared to mammals. Our experiments identify the sequence determinants for fly miRNA binding, which promise to spur the development of computational tools to accurately predict miRNA-mediated silencing in flies.

## Results

### Absolute equilibrium dissociation constants can be estimated from RBNS data

RNA Bind-n-Seq (RBNS) is a high-throughput sequencing method developed to study the affinity and specificity of RNA-binding proteins<sup>34</sup>. When combined with maximum-likelihood analysis, RBNS recapitulates equilibrium dissociation constants ($K_D$) for simulated data<sup>23</sup>, and miRNAs<sup>23</sup> and piRNAs<sup>35</sup> whose affinities have been determined by ensemble or single-molecule methods. To further test the validity of this approach, we applied the maximum-likelihood strategy to published RBNS data for human PUM2<sup>36</sup> to obtain $K_D$ = 0.32 ± 0.01 nM for the PUM consensus binding site, UGUAUAUA. This
result agrees well with the reported K_D values for human PUM2, 0.17 nM³⁷, fly Pumilio, 0.42 ± 0.07 nM³⁸, and *Saccharomyces cerevisiae* PUF4, 0.88 nM³⁹.

## Canonical binding can be predicted by free energy of base-pairing

miRNAs display sequence-specific differences in binding their canonical sites: those with strong predicted free energy of site pairing bind their target sites with higher affinity than miRNAs with weak seed-pairing²¹; McGeary et al., 2019, #16; Jouravleva et al., 2022, #143956}. Nevertheless, the difference in binding affinities of mammalian miRNAs is less than might have been expected. To study the energetics of canonical binding of fly miRNAs, we loaded recombinant Ago1 loaded with one of four different miRNAs—*let-7*, *bantam*, miR-184 and miR-11—chosen because they are abundant in S2 cells⁴⁰, play key roles in *Drosophila* development and homeostasis¹³,¹⁴,³⁰,⁴¹⁻⁴⁷, and span a range of GC content within their seeds and 3' regions (Fig. 1a). In agreement with previous studies in animals, all four miRNAs bound 8mer sites (targets with complementarity to positions g2–g8 and an adenosine opposite miRNA g1, i.e., t1A) with the highest affinity: K_D = 1.73 pM (95% CI = [1.73, 1.74]) for *let-7* to K_D = 18.9 pM (95% CI = [18.8, 19.1]) for *bantam* (Fig. 1b). The hierarchy of other canonical sites varied with the miRNA sequence. For *let-7* and miR-184, 7mer-m8 displayed a ~4-fold higher affinity than 7mer-A1; but for *bantam* and miR-11, the dissociation constants of 7mer-m8 and 7mer-A1 were almost identical. The ranking of 6mer, 6mer-m8 and 6mer-A1 was also miRNA-specific: K_D⁶mer < K_D⁶mer-m8 < K_D⁶mer-A1 for miR-184 but K_D⁶mer < K_D⁶mer-A1 < K_D⁶mer-m8 for *let-7*; for miR-11, the affinities of these three site types were indistinguishable. These results mirror those for mammalian miRNAs²²,²³. Moreover, direct binding measurements found no substantive difference in affinity between a seed-matching (K_D = 5 ± 3 pM) and a fully complementary target (K_D = 2 ± 1 pM; Fig. S1a), suggesting that seed complementarity dominates *Drosophila* Ago1 target binding, just like AGO2²¹,²²,⁴⁸⁻⁵⁰. Unlike in mammals, these differences can be predicted by existing
models of RNA duplex stability in solution. We focused on 7mer-m8, 6mer, and 6mer-m8 sites because they lack adenosine at position 1, which is stabilized within an Ago binding pocket and does not pair with the miRNA⁵¹. Calculated dissociation constants using the nearest neighbor free energy correlated with measured affinity values (Pearson's *r* = 0.669, *p*-value = 0.02; **Fig. 1c**), suggesting that canonical binding of *Drosophila* miRNAs can be inferred from base-pairing stabilities.

## Ago1 does not tolerate G:U pairs within the seed

*Drosophila* miRNAs have been proposed to repress mRNAs containing seed-matched binding sites interrupted by G:U wobble-pairs¹²,³⁰. However, these mRNAs also contain canonical binding sites free of G:U wobble pairs. Our RBNS experiments do not support the view that fly Ago1 tolerates G:U wobble pairs in the seed sequence. We measured the binding affinity of 8mer and 7mer-m8 binding sites containing one, two or three G:U wobble-pairs (**Fig. 2a, Fig. S1b**). A single G:U base-pair at positions t2–t7 reduced the binding affinity of 8mer and 7mer-m8 sites by ~15-fold. Binding sites with G:U wobble-pairing at the last position of a site type had dissociation constants comparable to the corresponding shorter site type: $K_{D,8mer-w8}^{let-7}$ = 15.4 pM vs. $K_{D,7mer-A1}^{let-7}$ = 22.1 pM, $K_{D,8mer-w8}^{miR-11}$ = 61.2 pM vs. $K_{D,7mer-A1}^{miR-11}$ = 81.2 pM, $K_{D,7mer-m8,w2}^{let-7}$ = 278 pM vs. $K_{D,6mer-m8}^{let-7}$ = 328 pM, $K_{D,7mer-m8,w2}^{miR-184}$ = 154 pM vs. $K_{D,6mer-m8}^{miR-184}$ = 321 pM, and $K_D$, $7mer-m8,w2^{bantam}$ = 866 pM vs. $K_{D,6mer-m8}^{bantam}$ = 1,013 pM. Sites with >1 G:U had $K_D$ values comparable to RNA containing no identifiable sites. That is, binding to targets with >1 G:U is indistinguishable from background (**Fig. 2a, Fig. S1b**). We conclude that G:U wobbles within the seed region are detrimental for Ago1 binding.

## Compensation by strong 3' pairing is limited to one imperfection within the seed

Validated targets of *bantam*, miR-2a, and miR-7 contain compensatory sites: 8mer sites with a single G:U pair compensated by a strong pairing to the miRNA 3' end conferred
repression in vivo<sup>12,14</sup>. RBNS is limited to studies of motifs ≤12-nt long, as longer motifs are poorly represented in the sequencing data<sup>22,23</sup>. We designed a *let-7* target RNA fully complementary to *let-7* but for a single G:U at g4, the position at which a wobble pair is most detrimental to seed binding (**Fig. 2b**, middle panel), and measured its binding affinity in a competition assay with a <sup>32</sup>P-radiolabeled target complementary to the entirety of *let-7*. The target bearing a single G:U pair displayed nearly the same affinity as the fully complementary target. In contrast, introduction of a second G:U pair at position g5 decreased its binding affinity 110-fold (**Fig. 2b**, right panel). We obtained similar results for binding sites bearing mismatched nucleotides instead of G:U pairs (**Fig. 2c**). Together, our data indicate that compensation by 3' pairing can rescue sites with no more than a single G:U or mismatch in the miRNA seed.

**The effect of target mismatches differs across the seed**

The seed region of miRNAs behaves as an RNA helix—mismatches in the center have the greatest effect, because they disrupt coaxial stacking more than mismatches at the extremities<sup>21,23,48</sup>. Consistent with this idea, single mismatches to seed positions g3, g4, and g5 led to the largest reduction in binding for *Drosophila Ago1* (**Fig. 3a**). At these positions mismatched nucleotides A and G are often the least tolerated, likely because their purine rings are larger than pyrimidines and thereby cause more steric hindrance.

Interestingly, miR-184-guided Ago1 displays an unusual behavior in binding mismatched targets. Like *let-7*, *bantam*, and miR-11, it binds 8mer targets with single mismatches at positions t4 and t5 less tightly than fully matched sites (17–69-fold increase in $K_D$ values). But its affinities for t4- and t5-mismatched targets were ≤ 200 pM, unexpectedly high compared to 8mer sites bearing a single mismatch at t3 or t6 (**Fig. 3a**). As expected, sites with t4 or t5 mismatched nucleotides have higher predicted $ΔG$ values than sites with t3 or t6 mismatches (**Fig. 3b**) and are not sequestered in stable secondary structures occluding their binding (**Fig. 3c**).
To better understand why miR-184 binds 8mer-x4 mismatched target sites with unexpectedly high affinity, we used AlphaFold 3⁵² to model the structures of Ago1•miR-184•target RNA for 8mer-x3, 8mer-x4, and 8mer-x5 sites. Surprisingly, AlphaFold 3 predicts that Ago1•miR-184 binds to mismatched 8mer sites with largely the same conformation as Ago1•miR-184 binds a canonical 8mer site (Fig. S2). Structural predictions of Ago1•let-7 bound to mismatched 8mer sites yielded the same results: Ago1•let-7•8mer-x3, Ago1•let-7•8mer-x4, and Ago1•let-7•8mer-x5 were quite similar to Ago1•let-7•8mer (Fig. S3), and therefore fail to explain the miRNA-specific differences in binding affinities. Our data suggest that Ago1 may bind sites containing one single central mismatch but identifying universal rules for predicting which miRNAs can bind 8mer-x4R sites with unexpectedly high affinity high-throughput target binding measurements for a larger set of miRNAs.

## Nucleation bulges can confer binding affinity similar to that of canonical sites

In mammals, target insertions and deletions in the seed increase $K_D^{21,23,53}$. An exception is nucleation-bulge sites identified by high-throughput crosslinking and immunoprecipitation in mouse brain⁵⁴. These 8mer sites consist of seven nucleotides paired to miRNA positions g2–g8 and one nucleotide opposing position g6 protruding as a bulge but sharing potential complementarity to miRNA position g6. Some mammalian miRNAs effectively bind nucleation-bulge sites in vitro²²,²³ and repress nucleation-bulge sites in cultured cells⁵⁴.

Like mammalian AGO2, fly Ago1 does not tolerate indels within the seed: small target deletions or 1-nt bulges reduced binding affinity by ~50–1,000-fold (Fig. 4a). Nevertheless, nucleation-bulge sites displayed binding affinities similar to those of canonical sites: $K_{D,8mer-b5.6A}^{let-7} = 120$ pM vs. $K_{D,6mer-A1}^{let-7} = 92$ pM, $K_{D,8mer-b5.6G}^{miR-11} = 107$ pM vs. $K_{D,7mer-A1}^{miR-11} = 70$ pM, and $K_{D,8mer-b5.6CA}^{miR-184} = 38$ pM vs. $K_{D,7mer-A1}^{miR-184} = 37$ pM.
pM (Fig. 4b). Like in mammals, nucleation bulges may constitute an alternative mode of
*Drosophila* miRNA target recognition that follows a pivot-pairing rule.

Repertoire of fly Ago1 target sites

In an RBNS experiment, Ago1 is incubated with a pool of 10¹² distinct RNA sequences.
Therefore, in addition to measuring binding affinities of specific sites of interest, RBNS
enables a de novo search for sites of productive binding²²,²³,³⁴,⁵⁵. As expected, this
approach identified canonical 8mer, 7mer-m8, 7mer-A1, 6mer and 6mer-m8 binding
sites (Fig. 5a). For *let*-7, it also identified short seed-matched sites 6mer-A1, 5mer-A1,
and 5mer-m2.6, as well as 8mer-w8 and 7mer-w8—sites bearing a G:U wobble at the
distal t8 position. Because fly Ago1 does not tolerate G:U pairing in the seed, these
8mer-w8 and 7mer-w8 likely correspond to 7mer-A1 and 6mer sites with favorable, AU-
rich flanking contexts (see below). Finally, motifs complementarity to positions g13–g16
were also detected. These likely correspond to 3' supplemental pairing for weak seeds
that are too variable to be detected by our analyses: e.g., 5-mer sites separated from
the supplemental pairing by loops of various sizes. The repertoire of binding sites for
miR-11 resembled that of *let*-7, except that two additional short seed-matched sites,
6mer-m4.9 and 5mer-m4.8, could be identified. Sites with 3' supplemental pairing were
not enriched above background in miR-184 and *bantam* datasets. miR-184 sites
included canonical, short seed-matched and 8mer-x4C—an 8mer site bearing a
mismatched t4 nucleotide with K_D ~130 pM (Fig. 3a). Overrepresented sites bound by
*bantam* included only canonical and 5mer-m2.6 sites, likely because the *bantam* seed is
predicted to pair more weakly with a seed-matched target than *let*-7, miR-11 or miR-184
and, therefore, cannot tolerate imperfections.
Fly Ago1 cleaves central sites and binds some 3'-only sites

Unlike high-throughput analysis of mammalian AGO2<sup>22,23</sup>, our RBNS experiments with fly Ago1 failed to detect central or 3'-only sites. Mammalian AGO2 can cleave targets with centered sites, seedless sites with 9-10 nucleotides complementarity to the center of the miRNA<sup>24</sup>. *Drosophila* Ago1 retains the ability to catalyze endonucleolytic cleavage of extensively matched target RNAs, and like other Argonaute proteins, cleaves the phosphodiester bond linking target nucleotides t10 and t11<sup>56-58</sup>. In theory, efficient cleavage of targets with centered sites might prevent their recovery in RBNS data. To test this idea, we performed in vitro cleavage assays with synthetic RNA targets containing two distinct 11-nt centered sites complementary to miRNA nucleotides g4-g14 (11mer-m4.14) or g5-g15 (11mer-m5.15). Ago1•let-7 cleaved both centered sites at levels comparable to those observed with a fully complementary RNA (Fig. 5b, Fig. S4). Therefore, cleavage of central sites likely prevents their recovery in RBNS libraries, making RBNS unsuitable for measuring their binding affinities. We note that AGO2-catalyzed mRNA cleavage of 11-12-nt-long centered sites requires Mg<sup>2+</sup> >2 mM<sup>24</sup>; in animals, the intracellular Mg<sup>2+</sup> concentration is < 1 mM<sup>59</sup>.

By contrast, some 3'-only sites were enriched in RBNS datasets but did not pass our criteria for significance (see Material and Methods). Therefore, we directly measured the affinity of sites with 10-nt segments of perfect complementarity to the miRNA sequence, scanning from position g9 to the 3' end of the miRNA (Fig. 5c). For *bantam*, miR-184 and miR-11, 10-mers that base paired to the guide 3' end bound with comparable or higher affinity than the canonical 6mer site. Except for the *bantam* 10mer-m14.23 site, motifs with more distal pairing had higher affinities than more seed-proximal sites: $K_{D,10mer-m9.18} = 587$ pM, $K_{D,10mer-m10.19} = 752$ pM, $K_{D,10mer-m11.20} = 571$ pM, $K_{D,10mer-m12.21} = 217$ pM, and $K_{D,10mer-m13.22} = 71$ pM vs. $K_{D,6mer} = 112$ pM. For *let-7*, none of the 10-mers conferred stronger binding than a canonical 6mer. Unlike canonical sites,
the miRNA-specific differences in the affinities for 3'-only sites did not correlate with
differences in dissociation constants calculated using the nearest neighbor free energy
(Pearson's r = 0.411, p-value = 0.08; Fig. 5d).

**Influence of flanking dinucleotide sequences**

The nucleotide composition of sequences immediately flanking miRNA sites significantly
influences mRNA repression in mammalian cells¹⁶,¹⁹,²¹,²²,⁶⁰. Local sequence context
similarly influences Ago1 binding affinity. We divided the *let-7* 8mer site into 4⁴ = 256
different 12-nt sites according to the dinucleotide sequences immediately flanking the 5'
and the 3' ends of the 8mer site and measured their *K*<sub>D</sub> values by RBNS. We used
RNAplfold⁶¹ to estimate the accessibility of each site by computing the probability of its
being unpaired at thermodynamic equilibrium. The predicted accessibility scores were
negatively correlated to measured binding affinities (Pearson's *r* = -0.352, p-value <
0.001; **Fig. 6**). For the 256 distinct flanking contexts, the *K*<sub>D</sub> values spanned a ~20-fold
range, with higher binding affinities corresponding to greater AU content in the flanking
dinucleotides.

We repeated our analysis with 8mer binding sites for *bantam*, miR-184, and
miR-11. As we observed for *let-7*, 8mer binding sites with low accessibility scores had
low binding affinities for all three miRNAs (**Fig. 6**). Finally, for every miRNA tested, we
divided 7mer-m8, 7mer-A1, 6mer, 6mer-m8, and 6mer-A1 binding sites into 256
different sites according to the dinucleotide sequences immediately flanking the 5' and
the 3' ends of each site type and measured their *K*<sub>D</sub> values by RBNS. The binding
affinities for nearly all site types correlated with accessibility scores. The exceptions
were *let-7*, *bantam*, and miR-11 binding to 6mer-A1 sites, and miR-11 binding to
7mer-A1 sites. These data suggest that *Drosophila* Ago1 competes with local RNA
secondary structures for site binding.
Discussion

Despite the importance of *D. melanogaster* as a model system, the targets of most fly miRNAs are largely unknown. The most successful prediction algorithm, TargetScan Fly v7 explains only a small fraction of changes in mRNA abundance caused by the introduction of a miRNA to S2 cells (coefficient of variation r² = 0.19)²⁵. Recent improvement of models predicting miRNA-mediated silencing in mammalian cells required quantitative, high-throughput measurements of miRNA binding affinities²¹,²². To date, most studies of fly miRNAs have used reporter assays in flies and examined repression efficacy of individual targets one-by-one¹³,¹⁴,²⁷. A reporter assay using *Drosophila* S2 cells monitored changes in steady-state levels of all cellular mRNAs after cell transfection with supraphysiological concentrations of exogenous miRNA duplexes²⁵. Higher-than-physiological miRNA concentrations may identify binding sites that are not functional in vivo. High-throughput sequencing methods that rely on UV crosslinking and immunoprecipitation yield comprehensive lists of RNA-binding motifs but do not enable quantitative assessment of binding affinities⁴⁰. Consequently, biochemically validated rules for predicting the targets of miRNAs in flies still do not exist.

The first step in constructing a predictive model requires quantitative measurements of binding affinities between miRNA-loaded Ago proteins and target sites. Higher affinity binding is expected to yield greater occupancy of a target site and therefore greater repression. We used RBNS to identify productive binding sites for four fly miRNAs. Our analyses using stringent statistical thresholds revealed that the repertoire of fly miRNA target sites is less complex than in mammals. Fly miRNAs bind canonical and seed-matched binding sites and poorly tolerate imperfections within the seed. Nevertheless, seed-matched sites with a single imperfection (mismatch, wobble pairing, 1-nt target deletion or 1-nt target insertion) could be compensated by extensive
pairing to the guide sequence, as suggested by reporter assays in flies¹⁴. Consistent
with this idea, motifs complementarity to guide nucleotides at g13–g16 were enriched in
*let-7* and miR-11 RBNS datasets. However, the maximum effective motif size for de
novo site discovery by RBNS is 10 nt, because reads with longer motifs are sparse in
the sequencing datasets. Therefore, identifying the minimal degree of complementarity
required to rescue weak canonical sites or seed-matched sites with imperfections in
flies will call for other experimental strategies such as RBNS modified to interrogate
bipartite sites³³ or screen large numbers of pre-designed RNA sequences using TIRF²¹.
Structural and biochemical studies of mammalian miRNAs revealed that the seed and 3'
supplementary regions can be bridged by target loops 7–15-nt long²¹,⁵³. If fly Ago1
provides a similar mechanism for extended miRNA targeting, compensatory sites in flies
may include a larger number of transcripts than previously estimated.

While fly miRNA binding is more restricted than in mammals, fly miRNAs bound
some non-canonical seed-matched sites with similar or greater affinity than a canonical
6mer site. One of these was the nucleation bulge site⁵⁴, which was bound by *let-7*,
miR-11, and miR-184, but not by *bantam*. Another example was a miR-184 binding site
with extended seed and a cytosine at position t4 (8mer-x4C). This site type was
productively bound only by miR-184; whether other miRNAs can bind seed-matched
sites with single nucleotide mismatches remains to be uncovered. Finally, our data
suggest that miRNAs may effectively target seedless 3'-only and central non-canonical
sites, as observed for mammalian miRNAs²²⁻²⁴.

The ability to measure binding affinities from RBNS datasets enabled us to obtain
*K_D* values for hundreds miRNA binding sites. Canonical binding sites of the four
miRNAs tested displayed miRNA-specific differences in their binding affinities. Unlike in
mammals, these differences could be predicted by nearest neighbor methods⁶². We
envision that our high-throughput measurements of binding affinities using RBNS may
enable prediction of changes in the occupancy of fly miRNA-guided Ago1 at sites
across the transcriptome in response to developmental stimuli, thereby allowing the
modeling of the resulting changes in regulatory activity.

Acknowledgments

We thank members of the Zamore and Jouravleva laboratories for critical comments on
the manuscript. This work was supported in part by National Institutes of Health grant
R35 GM136275 to P.D.Z. and by ATIP-Avenir funding (CNRS Biology) to K.J.

Author contribution

Conceptualization, K.J., J.V.B and P.D.Z.; Methodology, K.J. and J.V.B; Investigation, K.J. and J.V.B; Formal Analysis, K.J. and J.V.B; Writing – Original Draft, K.J. and J.V.B; Writing – Review & Editing, K.J., J.V.B and P.D.Z.; Supervision, K.J. and P.D.Z.; Funding Acquisition, K.J. and P.D.Z.

Competing interests

The authors declare no competing interests.
# Methods

## RNA

Ago1 was loaded with chemically synthesized (Sigma) guide and the passenger strands list in **Table S1**; each synthetic RNA was gel-purified before use. The siRNA duplexes were annealed for 1 min at 90°C, 1 h at 37°C and 10 min at room temperature (20-25°C) in 30 mM HEPES-KOH, pH 7.9, 100 mM potassium acetate, 2 mM DTT using a 1:1.25 molar ratio of guide-to-passenger.

A libraries of RNA oligonucleotides, each containing 20 central random nucleotides (Table S1), were synthesized (IDT) with an equal ratio of bases for each random position, 5' ³²P-labeled and gel-purified. DNA "blocker" oligonucleotides complementary to the common sequences present in each RNA molecule were synthesized (IDT) and annealed to the RNA library in 30 mM HEPES-KOH, pH 7.5, 120 mM potassium acetate, 3.5 mM magnesium acetate using a 1:1.2 molar ratio of RNA pool to DNA blockers; 5'-end and 3'-end blocking cDNA oligonucleotides #1 (Table S1) were used in RBNS for Ago1 loaded with *let-7*, *bantam*; 5'-end and 3'-end blocking cDNA oligonucleotides #2 were used in for Ago1 loaded with miR-184 (Table S1).

## Cell culture

*Drosophila* Schneider 2 (S2) cells (Gibco) were cultured in *Drosophila* Schneider's media (Gibco) supplemented with 10% FBS. Cells were maintained in a humidified incubator at 27°C and examined regularly to ensure absence of mycoplasma contamination.

## Generation of FLAG-Ago1 expressing cells

Ago1 cDNA was amplified by RT-PCR from total RNA extracted from *w*¹¹¹⁸ fly heads. The Ago1 coding sequence was cloned into pMT expression vector (Invitrogen), fusing Ago1 in-frame with an N-terminal FLAG tag. S2 cells (25 million, 70% confluent) were
transfected with 10 µg pMT-FLAG-Ago1 plasmid using 20 µl TransIT-Insect Transfection Reagent (Mirus Bio) according to manufacturer's instructions. After 18 h transfection, copper sulfate was directly added to the culture medium to a final concentration of 500 µM, and the cells were incubated for 30 h.

## RISC purification

FLAG-Ago1 expressing S2 cells were harvested; cell pellets were flash-frozen and stored at -80°C. Cell extract was essentially prepared as described⁶³. Briefly, the cell pellet was washed three times in ice-cold PBS and once in Buffer A (10 mM HEPES-KOH, pH 7.9, 10 mM potassium acetate, 1.5 mM magnesium acetate, 0.01% (w/v) CHAPS, 0.5 mM DTT, 1 mM AEBSF, hydrochloride, 0.3 µM Aprotinin, 40 µM Bestatin, hydrochloride, 10 µM E-64, 10 µM Leupeptin hemisulfate). Then, the pellet was resuspended in twice its volume with buffer A and incubated on ice for 20 min to allow the cells to swell. The cells were subsequently lysed with a Dounce homogenizer and a tight pestle (B type; 40 strokes) on ice. The homogenate was centrifuged at 2,000 × g to remove nuclei and cell membranes. Next, 0.11 volumes (that of the clarified supernatant from the low-speed centrifugation) of Buffer B (300 mM HEPES-KOH, pH 7.9, 1.4 M potassium acetate, 30 mM magnesium acetate, 0.01% (w/v) CHAPS, 0.5 mM DTT, 1 mM AEBSF, hydrochloride, 0.3 µM Aprotinin, 40 µM Bestatin, hydrochloride, 10 µM E-64, 10 µM Leupeptin, hemisulfate) was added, followed by centrifugation at 100,000 × g for 20 min at 4°C and the supernatant collected as the S100 extract. Finally, 0.32 volumes ice-cold Buffer C (30 mM HEPES-KOH pH 7.9, 120 mM potassium acetate, 3.5 mM magnesium acetate, 0.01% (w/v) CHAPS, 2 mM DTT, 1 mM AEBSF, hydrochloride, 0.3 µM Aprotinin, 40 µM Bestatin, hydrochloride, 10 µM E-64, 10 µM Leupeptin, hemisulfate) was added to the S100 to achieve a 20% (w/v) final glycerol concentration, followed by gentle inversion to mix. The S100 was aliquoted, frozen in liquid nitrogen, and stored at -80°C.
To assemble RISC, 3 ml S100 (~40 mg total protein) was incubated with 150 nM miRNA duplex for 1.5 h at 25°C in 30 mM HEPES-KOH pH 7.9, 120 mM potassium acetate, 3 mM magnesium acetate, 2 mM DTT, 1 mM ATP, 25 mM creatine phosphate, 30 µg/ml creatine kinase.

To capture RISC, 30 µl anti-FLAG M2 paramagnetic beads (Sigma) were used per ml of post-assembled extract, washed three times with 30 mM HEPES-KOH pH 7.9, 120 mM potassium acetate, 3 mM magnesium acetate, 0.05% (w/v) CHAPS, 2 mM DTT and incubated with assembled RISC with rotation at 4°C overnight. Beads were washed five times with wash buffer (30 mM HEPES-KOH, pH 7.9, 120 mM potassium acetate, 3 mM magnesium acetate, 2 mM DTT, 0.05% (w/v) CHAPS), and RISC was eluted from the beads with 100 ng/ml 3XFLAG peptide (Sigma) in 300 µl wash buffer for 1 h at room temperature. Elution was repeated two more times, and the three eluates combined. RISC was further purified via the by sequence affinity capture⁶⁴. Briefly, RISC was incubated with gentle rotation for 1 h at room temperature with 800 pM biotinylated, 2'-O-methyl capture oligonucleotide (Table S1) linked to streptavidin paramagnetic beads (Dynabeads MyOne Streptavidin T1, Life Technologies). RISC was eluted with 2 nmol biotinylated competitor oligonucleotide (Table S1) in 80 µl buffer composed of 30 mM HEPES-KOH pH 7.9, 1 M potassium acetate, 3.5 mM magnesium acetate, 0.05% (w/v) CHAPS, 20% (w/v) glycerol, 2 mM DTT for 2 h at room temperature. Excess competitor oligonucleotide was removed by incubating the eluate with 3.5 mg streptavidin paramagnetic beads (Dynabeads MyOne Streptavidin T1, Life Technologies) for 15 min at room temperature. Finally, RISC was dialyzed at 4°C against three changes (3 h each) of a 3,000-fold excess of storage buffer (30 mM HEPES-KOH pH 7.9, 120 mM potassium acetate, 3.5 mM magnesium acetate, 0.05% (w/v) CHAPS, 2 mM DTT, 20% (w/v) glycerol). RISC was aliquoted, frozen in liquid nitrogen, and stored at -80°C. For competition experiments (Fig. 2cd), RISC was assembled in *Drosophila* embryo lysate
from 0–8-h embryos prepared as described<sup>65</sup>; assembled RISC was purified as described above<sup>64</sup>.

## Quantification of purified RISC

Total concentration of RISC was estimated by measuring concentration of associated miRNA using Northern blotting as described<sup>66</sup>. Briefly, miRNA guide standards and RISC were first resolved on a denaturing 15% polyacrylamide gel, followed by transfer to Hybond-XL (Cytiva) nylon membrane by semi-dry transfer at 20 V for 1 h. Next, crosslinking was performed with 0.16 M 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide in 0.13 M 1-methylimidazole, pH 8.0, at 60°C for 1 h. The crosslinked membrane was pre-hybridized in Church buffer (1% (w/v) BSA, 1 mM EDTA, 0.5 M phosphate buffer, and 7% (w/v) SDS) at 37°C for 1 h. Next, 25 pmol 5' <sup>32</sup>P-radiolabeled RNA probe (<b>Table S1</b>) in Church buffer was added to the membrane and allowed to hybridize overnight at 37°C, followed by two washes with 1× SSC containing 0.1% (w/v) SDS for 5 min and two washes with 0.1× SSC containing 0.1% (w/v) SDS at 37°C for 15 min. The membrane was air dried and exposed to a storage phosphor screen.

The concentration of active RISC was measured by stoichiometric binding titration assays as described<sup>48</sup>. Binding reactions were performed in 5 µl in the presence of 30 mM HEPES-KOH, pH 7.9, 120 mM potassium acetate, 3.5 mM magnesium acetate, 2 mM DTT, 0.01% (w/v) CHAPS. Concentration of 5' <sup>32</sup>P-RNA target complementary to the seed region of the miRNA guide (<b>Table S1</b>) was 0.5 nM in all reactions, and the RISC concentrations spanned from 0.05–5 nM. The assay also included a mock binding reaction using RISC storage buffer. Binding reactions were incubated at 25°C for 1 h. RNA binding was measured by capturing protein-RNA complexes on Protran nitrocellulose membrane (Whatman, GE Healthcare Bioscience, Pittsburgh, PA) and unbound RNA on a Hybond-XL (Cytiva) nylon membrane with a Bio-Dot apparatus (Bio-Rad, Hercules, CA). After applying the sample under vacuum,
membranes were washed with 10 µl of equilibration buffer (30 mM HEPES-KOH pH 7.9, 120 mM potassium acetate, 3.5 mM magnesium acetate, 2 mM DTT). Membranes were air-dried and signals detected by phosphorimaging. To measure concentration of active, binding-competent RISC, titration data were fit to

$$f(r) = f_{max} \times \frac{r + K_{D} + n - \sqrt{(r + K_{D} + n)^{2} - 4 \times r \times n}}{2 \times n}$$

where $K_D$ is the apparent dissociation constant, r is the molar ratio of [RISC] to [RNA], n is the stoichiometric equivalence point, f is the fraction bound, $f_{max}$ is the maximum fraction bound.

## Competition assays

Competition reactions (5 µl) were performed in 18 mM HEPES-KOH, pH 7.4, 100 mM potassium acetate, 3 mM magnesium acetate, 5 mM DTT, 0.01% (v/v) IGEPAL CA-630, 0.01 mg/ml baker's yeast tRNA. Both 5' ³²P-RNA target fully complementary to the miRNA guide (Table S1) and RISC were 0.1 nM in all reactions. Concentrations of the competitor RNA (Table S1) were spanned from 0.02 nM–100 nM (target to *let*-7 with g2–21 complementarity), 0.05–1,000 nM (target to *let*-7 with g2–21 complementarity and a G:U pair at position 4), and 0.5–10,000 nM (all the other *let*-7 targets). The assay also included a no-RISC competition reaction using binding buffer. All reactions were incubated at 25°C for 1 h. The fraction bound was measured by capturing protein-RNA complexes on Protran nitrocellulose membrane (Whatman, GE Healthcare Bioscience, Pittsburgh, PA) and unbound RNA on a Nylon XL membrane (GE Healthcare Bioscience) using a Bio-Dot apparatus (Bio-Rad, Hercules, CA). The sample was placed on the top of the membranes and after applying vacuum, the membranes were washed with 10 µl of ice-cold wash buffer (18 mM HEPES-KOH, pH 7.9, 100 mM potassium acetate, 3 mM magnesium acetate, 5 mM DTT, 0.01 mg/ml baker's yeast
tRNA). Membranes were air-dried and signals detected by phosphorimaging. Data were fit to

$$ \theta = \frac{\left( [E_T] + [S_T] + K_D + \frac{K_D \times [C_T]}{K_C} \right) - \sqrt{\left( [E_T] + [S_T] + K_D + \frac{K_D \times [C_T]}{K_C} \right)^2 - 4[E_T] \times [S_T]}}{2 \times [S_T]} $$

where $[E_T]$ is total enzyme concentration, $[S_T]$ is total RNA target concentration, $K_D$ is the apparent equilibrium dissociation constant, $\theta$ is the fraction target bound in presence of competitor RNA with an apparent dissociation constant of $K_C$, $[C_T]$ is total competitor concentration.

## Measuring equilibrium dissociation constants by double filter-binding assays

Binding assays were performed as previously described⁴⁸ in 5 µl in equilibration buffer (25 mM HEPES-KOH, pH 7.9, 110 mM potassium acetate, 3.5 mM magnesium acetate, 2 mM DTT, 0.05 µg/µl BSA, 0.01 mg/ml baker's yeast tRNA, 8% (w/v) glycerol, 1 U/µl RNasin Plus). The 5' [³²P]-radiolabeled RNA targets (0.1 nM; Table S1) were incubated with a RISC concentration between 0.0008–0.8 nM RISC. The assay also included a control reaction using equilibration buffer. Binding reactions were incubated at 25°C for 2 h. RNA binding was measured by capturing protein–RNA complexes on Protran nitrocellulose (GE, GE10600002) and unbound RNA on a Hybond-XL (Cytiva, 45001151) in a Bio-Dot apparatus (Bio-Rad) as previously described⁶⁷. After applying the sample under vacuum, membranes were washed with 10 µl of wash buffer (25 mM HEPES-KOH, pH 7.5, 110 mM potassium acetate, 3.5 mM magnesium acetate and 2 mM DTT). Membranes were air-dried and signals detected by phosphorimaging.
Because $K_D$ < [RNA target], all binding data were fit to the following equation using IgorPro9.05 (WaveMetrics):

$$f = \frac{([E_T] + [S_T] + K_D) - \sqrt{([E_T] + [S_T] + K_D)^2 - 4[E_T][S_T]}}{2[S_T]}$$

where f is the fraction target bound, $[E_T]$ is the total RISC concentration, $[S_T]$ is the total RNA target concentration and $K_D$ is the apparent equilibrium dissociation constant.

## RNA Bind-n-Seq for de novo site discovery and $K_D$ measurements

RBNS were essentially performed as described$^{23,67}$. Each experiment included five or six binding reactions. The highest concentration of RISC used corresponded to 40% (v/v) of the stock solution and equaled 4.0–5.8 nM (f.c.) active protein. For additional reactions, the stock was serially diluted 3.2-fold in storage buffer. Each experiment also included a mock binding reaction (no-RISC control) using protein storage buffer without RISC. For each miRNA, we performed an additional binding reaction using protein storage buffer with miRNA guide at the highest miRISC concentration assayed, but lacking Ago1 protein. All binding reactions (20 µl) were performed in 20 mM HEPES-KOH, pH 7.9, 100 mM potassium acetate, 3.5 mM magnesium acetate, 0.05% (w/v) CHAPS, 2 mM DTT, 8% (w/v) glycerol, and contained 100 nM (f.c.) RNA library. To reduce non-specific binding, each reaction also included 0.05 µg/µl BSA and 0.01 mg/ml baker's yeast tRNA. Reactions were incubated for 2 h at 25°C and then filtered through a Protran nitrocellulose membrane (Whatman, GE Healthcare Bioscience, Pittsburgh, PA) on top of a Hybond-XL (Cytiva) nylon membrane in a Bio-Dot apparatus (Bio-Rad, Hercules, CA). To reduce retention of free single-stranded RNA, we pre-conditioned nitrocellulose and nylon membranes prior to use as described$^{68,69}$. Nitrocellulose filters were pre-soaked in 0.4 M potassium hydroxide for 10 min. Nylon filters were incubated in 0.1 M EDTA, pH 8.2 for 10 min, washed three times in 1 M sodium chloride for 10 min
each followed by a quick rinse (~15 s) in 0.5 M sodium hydroxide. Nitrocellulose and nylon filters were then rinsed in water until the pH returned to neutral and equilibrated in wash buffer (20 mM HEPES-KOH, pH 7.9, 100 mM potassium acetate, 3.5 mM magnesium acetate, 2 mM DTT) for at least 1 h at 25°C. After applying the sample under vacuum, membranes were washed with 100 µl wash buffer for 3 s. Membranes were air-dried and signals detected by phosphorimaging to monitor binding. The nitrocellulose membranes containing RISC-bound RNA were excised and incubated with 1 µg/µl Proteinase K (Thermo Fischer) in 100 mM Tris-HCl, pH 7.5, 10 mM EDTA, 150 mM sodium chloride, 1% (w/v) SDS, and 0.05 µg/µl glycogen for 1 h at 45°C shaking at 300 rpm. After phenol-chloroform extraction and ethanol precipitation, RNA was denatured at 90°C for 1 min, annealed to BRTP primer (Table S1) and reverse transcribed using SuperScript III (Life Technologies). RNA was degraded by alkaline hydrolysis using 0.4 M sodium hydroxide for 1 h at 55°C, and cDNA was recovered by ethanol precipitation. The sample was then amplified with AccuPrime Pfx DNA Polymerase (Invitrogen). The reactions were run on a 2% agarose gel, amplicons were purified, then sequenced using a NextSeq 500 (Illumina) to obtain 75-nt, single-end reads.

Only Illumina reads containing TGG (the first nucleotides of the 3' adapter) at positions 21–23 were analyzed. Sequences were filtered (Phred quality score ≥20 for all nucleotides, and “N” base calls disallowed), and the 3' adapter sequence (5' TGG AAT TCT CGG GTG CCA AGG 3') removed.

Occurrences of all 10-nt long motifs (10-mers) were counted in all the reads of each RBNS sample. These counts were then divided by the total count of all 10-mers to give motif frequencies. Enrichment of a motif was computed as the ratio of the motif frequency in the protein-bound samples over the frequency in the RNA pool. Z-score of a motif was computed as $Z = \frac{R - \bar{R}}{S}$ where R is enrichment of the motif, $\bar{R}$ is the mean of enrichment values of all 10-mers, and S is the sample standard deviation of enrichment
values of all 10-mers. A motif was considered significant if its Z-score was ≥99.9 percentile.

Enrichments in the library from the binding reaction with the greatest RISC concentration were used for the following iterative procedure: (1) enrichment values of all 10-mers were calculated; (2) the hundred most enriched 10-mers were interrogated for base-pairing with the guide miRNA; (3) the most enriched site type was identified; (4) Z-scores of motifs belonging to the site type were compared to the Z-score threshold; (5) all reads containing the binding site were masked in the RISC-bound library and the RNA pool so that stepwise enrichments of subsequent 10-mers could be used to eliminate subsequent 'shadow' motifs; (6) all enrichment values were then recalculated on the masked read sets to obtain the resulting most enriched 10-mers. This process continued until the Z-score of the most enriched binding site (calculated from the original enrichment values) was < 99.9th percentile.

To identify a binding site at each iteration, the one-hundred most enriched 10-mers were tested for base-pairing with the guide RNAs. If perfect complementarity was not observed, the 10-mer was tested for any of the following in this order: (1) complementarity to nine contiguous miRNA positions, allowing a single bulged target nucleotide; (2) complementarity to ten contiguous miRNA positions while allowing for wobble pairing; (3) complementarity to ten contiguous miRNA positions while allowing a non-wobble mismatch. If none of these configurations allowed assigning the motif to a binding site, the procedure was repeated with two 9-mers within the 10-mer, the three 8-mers within the 10-mer, etc., until a configuration of base-pairing was identified.

Each sequencing read in RNA pool and RISC-bound libraries was interrogated for presence of all binding sites of interest. The entire single-stranded sequence was interrogated: the 20-nt random-sequence region flanked by constant primer-binding sequences in the case when blockers were not used and the 20-nt random-sequence region flanked by 4 or 6 nucleotides of constant primer-binding sequence on either side
in the case when blockers were annealed to the RNA pool. A read was assigned to a
site category if it contained one single binding motif. Reads containing multiple
instances of binding sites (from the same or a different site category) and reads
containing partially overlapping sites were not included in the analysis and represented
≤1% of libraries. Reads that did not have any of binding motifs of interest were classified
as reads with a no-site. To estimate K<sub>D</sub> values, run the code<sup>23</sup> by following instructions
in the README file.

AlphaFold 3 predictions

To obtain the predictions by AlphaFold 3<sup>52</sup>, we directly submitted the jobs in the
alphafoldserver.com webserver and considered the best model (model 0) out of five
predictions based on its default self-estimation scores.

Data availability

RBNS sequencing data have been deposited at National Center for Biotechnology
Information Sequence Read Archive and are publicly available using accession number
PRJNA1185003.

Code availability

This study did not generate new code.
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**Main figure titles and legends**

**Fig. 1** | RNA Bind-n-Seq (RBNS) measures binding affinities of canonical target sites. (a) Overview of RBNS. Right: miRNA sequences used in Ago1 loading. (b) $K_D$ values fitted for canonical target sites. Error bars indicate 95% CI of the median. Right panel: pairing of target sites. (c) The relationship between the observed and predicted $K_D$ values for t2–t8, t2–t7, t2–t6 and t3–t8 binding sites of *let-7*, *bantam*, miR-184, and miR-11. *r* and *p*-values were calculated using Pearson correlation.

**Fig. 2** | The effect of G:U pairs within the seed on miRNA binding affinity. (a) $K_D$ values for canonical seed-matched sites (left: t2–t8 targets with t1A; right: t2–t8 targets) and one, two and three G:U pairs within *let-7* seed at indicated positions. Shown for comparison: 8mer, 7mer-m8, 7mer-A1, and 6mer-m8. Error bars indicate 95% CI on the median. The equilibrium dissociation constant of *let-7*-loaded Ago1 for the competitor bearing G:U base-pairs (c) or mismatches (d) within the seed, relative to that of a fully complementary target. miRNA sequence shown in red.

**Fig. 3** | The effect of target mismatches on miRNA binding affinity. (a) $K_D$ values for t2–t8 targets with t1A and different one-nucleotide mismatches at indicated positions. Error bars indicate 95% CI of the median. Dissociation constants calculated using the nearest neighbor free (b) and accessibility scores (c) for miR-184 t2–t8 targets with t1A and different one-nucleotide mismatches at indicated positions.

**Fig. 4** | $K_D$ values for t2–t8 targets with t1A and one-nucleotide deletions (a) and bulges (b) at indicated positions. Error bars indicate 95% CI of the median.

**Fig. 5** | Sequence-specific differences in miRNA affinities. (a) Site types identified by de novo site discovery in Ago1 *let-7*, miR-184, miR-11, and *bantam* RBNS and their fitted dissociation constants. (b) Representative denaturing polyacrylamide gel
electrophoresis showing cleavage of centered sites 11mer-m4.15 and 11mer-m5.15 by
*let-7-loaded Ago1.* (c) Dissociation constants for 3'-only sites. Horizontal dashed lines
indicate *K*<sub>D</sub><sup>8mer</sup>, *K*<sub>D</sub><sup>6mer</sup>, and *K*<sub>D</sub><sup>6mer-m8</sup>. Error bars in (a) and (c) indicate 95% confidence
intervals of the median. (d) The relationship between the observed and predicted *K*<sub>D</sub>
values for t9-t18, t10-t19, t11-t20, t12-t21, and t13-t22 binding sites of the four
miRNAs. *r* and *p*-values were calculated using Pearson correlation.

**Fig. 6** | The influence of flanking dinucleotide sequences. Relationship between the accessibility score and *K*<sub>D</sub> values for the 256 sites containing one canonical target site flanked by each of the dinucleotide combinations. Our analysis included 8mer, 7mer-m8, 7mer-A1, 6mer, 6mer-m8, and 6mer-A1 for all four miRNAs. *r* and *p*-values were calculated using Pearson correlation.
## Supplementary Figure Titles and Legends

**Fig. S1** | The effect of G:U pairs within the seed on miRNA binding affinity. (a) Equilibrium binding assays of Ago1•/et-7 for seed-matching and fully complementary target RNA using double-filter binding assay. (b) $K_D$ values for canonical seed-matched sites (left: t2–t8 targets with t1A; right: t2–t8 targets) and one, two and three G:U pairs within *bantam*, miR-11, and miR-184 seed at indicated positions. Shown for comparison: 8mer (cyan), 7mer-m8 (orange), 7mer-A1 (blue), 6mer-A1 (purple) and 6mer-m8 (gray). Error bars indicate 95% CI on the median.

**Fig. S2** | Structures of Ago1•miR-184 bound to t3-, t4-, and t5-mismached 8mer sites predicted by AlphaFold 3.

**Fig. S3** | Structures of Ago1•/et-7 bound to t3-, t4-, and t5-mismached 8mer sites predicted by AlphaFold 3.

**Fig. S4** | Ago1 cleaves centered sites in vitro. (a) Uncropped image of polyacrylamide gel electrophoresis shown in **Fig. 5b**. Sequence-specific cleavage was blocked when the target RNA contained a phosphorothioate linkage (orange) flanked by 2'-O-methyl ribose at positions t10 and t11 (red). (b) Ago1•/et-7 cleaved both centered sites at levels comparable to those observed with a fully complementary RNA. Cleavage reactions were performed with 3.5 nM Mg$^{2+}$ and contained 0.32 nM Ago1•/et-7 and 5 nM (a) or 100 nM (b) RNA target.
<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>
<figure><img src="image_6.png" /><figcaption>Vega-Badillo et al., Figure 2</figcaption></figure>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>
a

let-7

<figure><img src="image_9.png" /></figure>

miR-11

<figure><img src="image_10.png" /></figure>

bantam

<figure><img src="image_11.png" /></figure>

miR-184

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b

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c

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a

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b

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<figure><img src="image_22.png" /><figcaption>**miR-184** 5'- UGGACGGAGAACUGAUAAGGGC-3'</figcaption></figure>

<figure><img src="image_23.png" /><figcaption>**miR-11** 5'-CAUCACAGUCUGAGUUCUUGC-3'</figcaption></figure>

<figure><img src="image_24.png" /><figcaption>**bantam** 5'-UGAGAUCAUUUUGAAAGCUGAUU-3'</figcaption></figure>

<figure><img src="image_25.png" /><figcaption>**b**</figcaption></figure>

<figure><img src="image_26.png" /><figcaption>**c**</figcaption></figure>

<figure><img src="image_27.png" /></figure>

Starting position of 10-mer site

<figure><img src="image_28.png" /><figcaption>**d**</figcaption></figure>

Predicted K<sub>D</sub> (pM)
<figure><img src="image_29.png" /><figcaption>Vega-Badillo et al., Figure 6</figcaption></figure>
<figure><img src="image_30.png" /><figcaption>Vega-Badillo et al., Fig. S1</figcaption></figure>

<figure><img src="image_31.png" /></figure>
<figure><img src="image_32.png" /></figure>

miR-184-loaded Ago1

<figure><img src="image_33.png" /></figure>

<figure><img src="image_34.png" /></figure>

<figure><img src="image_35.png" /></figure>

<figure><img src="image_36.png" /></figure>

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<figure><img src="image_41.png" /></figure>
<figure><img src="image_42.png" /></figure>
<figure><img src="image_43.png" /><figcaption>Vega-Badillo et al., Fig. S4</figcaption></figure>

<figure><img src="image_44.png" /></figure>