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Timing of neurogenesis through sequential accumulation of miR-9 due to additive expression of multiple alleles

MicroRNAs (miRs) have important quantitative roles in tuning dynamical gene expression. Hes/Her transcription factor dynamics are sensitive to the increasing amount of miR-9 in the cell, transitioning from noisy high-level expression to oscillatory expression and then to downregulation. However, the mechanism by which miR-9 is quantitatively controlled is not known. In vertebrates, several distinct genomic loci produce the same mature miR-9, but the functional significance of multiple primary transcripts remains unknown. Here, we show that the amount of mature miR-9 increases during zebrafish neurogenesis in a sharp stepwise manner. We characterize the spatiotemporal profile of 7 distinct pri-mir-9s and show that they are sequentially expressed during hindbrain neurogenesis. Quantitative analysis of expression at the single-cell level, shows that expression of late-onset pri-mir-9-1 is added on, rather than replacing the expression of early onset pri-mir-9-4 and 9-5. Mutating the late-onset pri-mir-9-1 with CRISPR/Cas9 prevents the developmental increase of mature miR-9 and reduces late neuronal differentiation. Finally, we use mathematical modelling to explore possible benefits of a stepwise increase of miR-9 over a linear increase. We find that an adaptive network containing Her6 can be insensitive to a linear increase in miR-9 and show that such adaptation can be overcome by step-wise increases of miR-9. In conclusion, our work suggests that a sharp stepwise increase of mature miR-9 is contributed by sequential temporal activation of distinct loci. This may be a strategy to overcome adaptation and facilitate a transition to a new state of Her6 dynamics or level.


Introduction 42
MicroRNAs are a class of small (∼22 nucleotides) regulatory non-coding RNAs, 43 which regulate gene expression at the post-transcriptional level. These small RNAs 44 are processed from large microRNA primary transcripts (pri-mir) into 70∼90nt pre-45 cursors (pre-mir) before further splicing into ~22nt mature microRNA (miR). miR-9 is 46 a highly conserved microRNA that is expressed predominantly in the central nervous 47 system (CNS) of vertebrates and plays a crucial role during CNS development. 48 Specifically, previous work in Xenopus, zebrafish and mice has shown that miR-9 is 49 essential for cell fate transitions during neurogenesis (Shibata et al., 2011) (Coolen 50 et al., 2013) (Bonev et al., 2011Bonev et al., 2012). miR-9 post-transcriptionally tar-51 gets many transcription factors that are involved in neural development such as 52 FoxG1 (Shibata et al., 2008), Tlx (Zhao et al., 2009)  The Hes/Her family of proteins are expressed dynamically in an oscillatory manner at 58 the ultradian timescale (Hirata et al., 2002) (Shimojo et al., 2008. Hes/Her oscilla-59 tions are achieved by a negative feedback loop, whereby Hes/Her proteins inhibit 60 their own transcription coupled with a rapid turnover of protein and mRNA. Instability 61 of both protein and mRNA allows for levels of the protein to fall, de-repression to oc-62 cur and expression to resume, generating a cyclic pattern (Hirata et al., 2002) (No-63 vak and Tyson, 2008). Indeed, both mRNA and protein of Hes family genes are un-64 stable, for example, in mice, the half-life of Hes1 mRNA is ~24 minutes; the Hes1 protein half-life is in the order of 22 minutes (Hirata et al., 2002) and the Her6 ( Hes1 66 Zebrafish orthologue) protein half-life is around 10 minutes (Soto et al., 2020). 67 68 Ι nstability of mRNA, as well as translation of protein, are partly controlled by mi-69 croRNAs. Indeed, our previous work revealed that miR-9 regulation is important for 70 controlling Hes1 mRNA stability and allowing the oscillatory expression of Hes1 to 71 emerge. We have recently shown that in zebrafish, the dynamics of Her6 protein ex-72 pression switch from noisy to oscillatory and then to downregulation and that these 73 changes coincide temporally with the onset of miR-9 expression in the hindbrain 74 (Soto et al., 2020). When the influence of miR-9 on her6 is removed experimentally, 75 Her6 expression does not evolve away from the "noisy" regime and is not downregu-76 lated with a consequent reduction in progenitor differentiation. We have interpreted 77 this to mean that the miR-9 input is necessary to constrain gene expression noise, 78 enabling oscillations to occur and to be decoded by downstream genes which in turn 79 participate in downregulating Her6 as cells differentiate (Soto et al., 2020). 80 81 However, not only the presence of miR-9 but also the amount of miR-9 present is 82 important, as too much or too little miR-9 can lead to dampening of Hes1 oscillations 83 (Bonev et al., 2012) (Goodfellow et al., 2014. Indeed, mathematical modelling 84 showed that increasing miR-9 over time drives the Hes1 expression into different 85 states (oscillatory or stable high/low) and that the amount of miR-9 present in the cell 86 determines the length of time by which Hes1 oscillates, effectively timing the transi-87 tion to differentiation (Phillips et al., 2016) (Goodfellow et al., 2014. Together these 88 findings support that Hes/Her dynamics and downregulation are sensitive to the amount of mature miR-9 present in the cell; however, the mechanism by which miR-90 9 level is controlled is not known. 91 92 This question is complicated by the observation that vertebrates (and some inverte-93 brates) possess multiple copies of the miR-9 gene at distinct loci which are all capa-94 ble of producing the same mature microRNA. For example, both human and mouse 95 contain 3 copies of miR-9 (Rodriguez-Otero et al., 2011;Shibata et al., 2011) and 96 frogs have 4 (Walker and Harland, 2008). Due to an additional round of whole-97 genome duplications in teleost fish (Amores et al., 1998) (Jaillon et al., 2004, zebraf-98 ish have 7 paralogues of miR-9 (pri-mir-9-1 to pri-mir-9-7) (Chen et al., 2005). 99 100 One possibility is that different genomic loci contribute to miR-9 regulation in a quali-101 tative way, with differential temporal and spatial specificity of mature miR-9 expres-102 sion. Indeed, there is some limited evidence that these discrete copies of miR-9 are 103 expressed differentially during development both temporally and spatially (Nepal et 104 To explore the identity of the triple pri-mir-9 expressing progenitors, we turn our at-264 tention to the Dorso-Ventral (D-V) progenitor axis of the ventricular zone. The 265 everted structure of the zebrafish hindbrain means that dorsal progenitors are lo-266 cated more laterally than medial or ventral ones ( Fig. 4D; schematic). We com-267 pared the expression to neurog1, ascl1 and atoh1 which are markers for ventral, 268 medial and dorsal progenitors, respectively ( Fig. 4E) (Tambalo et al., 2020).  markably, at early stages of development the cells expressing two primary tran-270 scripts were mostly localized in the ventral progenitor region of the ventricular zone 271 ( Fig. 4A) while at later stages the cells with three primary transcripts exclude the 272 ventral most domain (Fig. 4B, C), suggesting that miR-9 high levels are required in 273 medial and dorsal progenitors. Pri-mir-9-5 was expressed throughout the everted 274 dorsoventral axis (Fig. 4B, D, F) and was co-expressed with her6 and her9, both of 275 which are expressed in the progenitor domain (mainly medial and some dorsal) and 276 are downregulated as cells differentiate. Both contain miR-9 binding sites and are 277 candidates for dynamic regulation by miR-9 ( Fig. 4F) (Coolen et al., 2013;Leucht et 278 al., 2008;Soto et al., 2020). 279 280 Knocking out the late pri-mir-1 preferentially affects neuronal differentiation 281 from medial progenitors. 282 The spatial analysis above showed that the expression of pri-mir-9-1 is added onto 283 to pre-existing pri-mir-9-4 and 9-5 expression in the medial and dorsal progenitors. 284 To find out whether there is any specificity in deleting pri-mir-9-1 we designed a 285 CRISPR/Cas9 based knock-down with guides that were specific to pri-mir-9-1 ( Fig.  286 5A, Fig. S4A-C). This resulted in reduction on mature miR-9 and pri-mir-9-1 from 287 37hpf onwards when the endogenous locus is transcribed ( Fig. 5B-C). RT-qPCR was also performed to pri-mir--9-3, 9-4 and 9-5 under mutation of pri-mir-9-1. Some 289 reduction (with high variability between samples) was also observed in pri-mir-9-4 290 and 9-5 but it was not maintained at later stages of development ( Fig. S4E-F,  291 48hpf). Pri-mir-9-3 was not affected (Fig. S4D). 292 Exploring the potential defect further we used a panel of differentiation markers 293 spanning the D-V axis (Fig. 5D). Injected fish did not show overt abnormalities; how-294 ever, RT-qPCR analysis at 3 dpf showed that the differentiation marker elavl4 was 295 reduced (Fig. 5E). This analysis also showed a reduction of noradrenergic neurons 296 (NAN) derived from medial progenitors (dbmx1a, Medial progenitors express her6 and her9 (Fig. 4F) which are miR-9 targets and 300 need to be downregulated before the cells can differentiate. In addition, me-301 dial/dorsal progenitors differentiate later in vertebrate development than ventral ones 302 (Delile et al., 2019). Therefore, our findings suggest that the late activation of pri-mir-303 9-1 contributes to the increase of miR-9 needed to downregulate Her6/Her9 in late 304 neural progenitors so that they can give rise to a spatiotemporally appropriate neu-305 ronal fate. 306 307 A miR-9 stepwise increase may be required to overcome adaptation of down-308

stream target expression 309
Having shown that the increase in miR-9 in development is functionally important for 310 differentiation, we wanted to explore whether the shape of the increase is also impor-311 tant. In other words, whether the way that miR-9 increases in steps can be decoded. 312 This was motivated by the biological evidence obtained from smiFISH and RT-qPCR experiments in which we observe a stepwise sharp increase of the primary tran-314 scripts (Fig. 6A) and the mature miR-9 (Fig. 1B) over time. We use a mathematical 315 model to ask whether a simple network of gene interactions can differentially re-316 spond to stepwise increase of miR-9 rather than a gradual increase. 317 Biological systems need to be robust to stochastic fluctuations that are due to low 318 copy number, or to random perturbations in the surrounding environment. This is re-319 ferred to as adaptation in the context of a particular output of interest, making the 320 biological system resistant to changes of the input. However, some changes of sig-321 nals are not simply due to noise or environmental fluctuations, and adaptive systems 322 may therefore also have to respond to specific signals under changing conditions, 323 especially during development, in order to move into a new state. Specifically, we 324 show how a stepwise change in gene expression can allow a system to move out of 325 an adaptively stable state. Since incoherent feed-forward loops (IFFL) are common 326  Table S14). Mathematically, we say that Her6 334 adapts perfectly to changes in miR-9 since, in this model, the steady state of Her6 is 335 independent of miR-9 (Methods Mathematical modelling (a)). The speed of this ad-336 aptation is controlled by the difference in reaction speed of the direct and indirect in-337 teractions between miR-9 and Her6. If the direct interaction is much faster than the indirect interaction, Her6 returns to steady state slowly after miR-9 copy numbers are 339 perturbed. However, if the indirect interaction is faster, adaptation occurs quickly. 340 341 Such perfect adaptation is beneficial because it allows stable mean expression of 342 Her6 in the presence of fluctuations of miR-9 expression (Fig. S5B,C). Conversely,343 no changes in miR-9, i.e linear or stepwise, can lead to persistent downregulation of 344 Her6. Since Her6 is downregulated in response to increasing miR-9 levels during 345 development, there would need to be an additional mechanism that enables the con-346 trolled escape from perfect adaptation. To investigate this, we extended our model to 347 include such a potential mechanism (Fig. 6B). Specifically, we introduce a down-348 stream target of Her6, named ܻ , which self-activates and interacts with Her6 through 349 mutual repression (as we have already previously hypothesised in (Soto et al., 350 2020). The different behaviours of this system can be seen in Fig. 6C

-D. A linear in-351
crease in miR-9 leads to an initial repression of Her6, which then proceeds to return 352 to its unperturbed steady state, due to the perfect adaptation ( Fig. 6C, Fig. S6A). 353 However, following a sharp increase of miR-9, the concentration of Her6 decreases 354 more strongly. This is sufficient for ܻ to overcome the repression from Her6, so that it 355 can self-activate and in turn repress Her6 into a new, lower steady state (Fig. 6D, 356 number of microRNA expressed from multiple loci is possibly due to the teleost-373 specific whole-genome duplication (WGD). Evidence from rainbow trout also shows 374 that following the salmonid-specific extra round of WGD, microRNAs appear to be 375 retained at higher levels than protein-coding genes (Berthelot et al., 2014). This may 376 suggest that extra copies of microRNA are evolutionary advantageous. Here, we 377 propose that retention of multiple microRNA loci could have specific functional ad-378 vantages for regulatory control of target gene expression of an organism. By examin-379 ing in detail, the temporal and spatial expression at single cell level of 3 selected 380 early and late pri-mir-9s, from across their phylogenetic tree, we offer two possible, 381 not-mutually exclusive, explanations for this multi-site organisation or primary tran-382 scripts. 383 384 The first explanation involves a qualitative mechanism. In this scenario, distinct pri-385 mir-9s have different spatial expression, which allows them to target different, i.e., 386 region-specific, gene expression. Some differences in the spatial expression of pri-387 mir-9s are easily discernible at low resolution (e.g., differential expression in the 388 forebrain) while others are subtle and require post-hybridisation sectioning to docu-389 ment, as we have done here. An example of the latter is the expression of pri-mir-9-1 390 which extents more dorsally in the hindbrain than pri-mir-9-4 at a late stage of devel-391 opment. This correlates well with the expression of Her6 and Her9, which are both 392 miR-9 targets but are expressed adjacent to each other along the D-V axis (Soto et 393 al., 2020). 394

395
The second explanation favours a quantitative mechanism. In this scenario, the dif-396 ferential temporal expression, where some primary transcripts commence their ex-397 pression early while others are only expressed late, results in the simultaneous ex-398 pression of both (or more) transcriptional loci in the same cells at a particular time in 399 development. In support of this scenario, we have shown by smiFISH that pri-mir-9-400 1, a late onset primary transcript, is co-expressed in the same cells as the earlier on-401 set pri-mir-9-4 or 9-5. This co-expression may be a strategy to increase the amount 402 In other cases where multiple paralogues of a microRNA have been described, dif-426 ferential and non-mutually exclusive qualitative and quantitative regulation may also 427 take place. For example, a recent study found that miR-196 paralogues show both 428 unique and overlapping expression (Wong et al., 2015). In this study, single KOs 429 showed some unique phenotypes (qualitative mechanisms) but combinatorial KOs 430 showed better penetrance and additional defects, suggesting an additive role of miR-431 196 paralogues in establishing vertebral number (quantitative mechanism). 432 433 A salient finding from our analysis is that the increase in the amount of miR-9 pre- and homeostasis (Khammash, 2021), a mechanism must exist to be able to over-445 ride it. We suggest that in the case of miR-9, a sharp, non-linear, increase may be 446 needed to push a dynamical system into a new state and this may be associated 447 with a cell fate change. In our case, we suggest that the increase of miR-9 during 448 development serves to drive the dynamics of Her6 (and other targets) from one state 449 to another, which in turn is important for the sequential acquisition of cell fates. 450 At present, our computational model is qualitative, rather than quantitative, and the 451 identity of some interacting genes in the network motif are not known. Nevertheless, 452 this model was conceptually useful to illustrate the existence of a system that can 453 decode and distinguish between specific upstream signalling profiles. Interestingly, 454 microRNAs are very commonly involved in transcription factor network motifs 455 (Minchington et al., 2020), including IFFLs (Tsang et al., 2007). A fully parameterized 456 model based on experimental evidence and identification of the unknown compo-457 nents/genes would be needed before it can be tested further. 458

459
In conclusion, by providing evidence for both a quantitative and qualitative mecha-460 nism, we have shed light on the possible roles of organising pri-mir-9s in several dis-461 tinct genomic loci, which may have led to their evolutionary conservation. An added benefit of our work is that the detailed characterisation we have described here will 463 enable the selection of the correct genomic locus for genetic manipulation of miR-9 464 production, depending on the precise spatio-temporal expression.  504   Table S3 for respective primers). and 50ng cDNA. Reactions were run on Step One 505 Plus Real-time PCR System (Applied Biosystems) alongside negative controls The 506 data for each sample was normalized to the expression level of U6 snRNA for ma-507 ture miR-9 or b-actin for pri-miR9s and analysed by the 2 −ΔΔCt method. 508 For each primer pair, the PCR product was examined by gel electrophoresis and its 509 melting curve to ensure a single fragment of the predicted molecular weight. 510 511

Whole mount chromogenic and fluorescence in situ hybridization and section-526
ing 527 Chromogenic in situ hybridisation was performed as previously described by Chris-528 tine Thisse (Thisse and Thisse, 2008) The smiFISH probes were designed using the probe design tool at 545 http://www.biosearchtech.com/stellarisdesigner/. The software can assign varied 546 size of probes, 18-22 nt, therefore we gave a size of 20nt for all designed probes 547 with the maximum masking level available for zebrafish. Using the respective pri-mir-548 9 sequence we designed 36 probes for pri-mir-9-1, 35 probes for pri-mir-9-4 and 35 549 probes for pri-mir-9-5. Using the respective gene mature mRNA sequence, we de-550 signed 29 probes for her6, 33 probes for her9, 40 probes for neurog1, 39 probes for 551 atoh1a and 40 probes for ascl1a (Table S5-S12, respectively). The designed 552 probes were X-FLAP tagged (5'CCTCCTAAGTTTCGAGCTGGACTCAGTG3') at the 553 5' of each gene-specific sequence. The gene specific probes were ordered from IDT 554 in a 96 well format in nuclease-free water, 100μM concentration. Upon arrival, we 555 combined 100 μl of the gene-specific probe together, mixed, split into 100 μl aliquots 556 and stored at -20°C. In addition, we ordered fluo-FLAP sequences 557 (5'CACTGAGTCCAGCTCGAAACTTAGGAGG3') from either IDT or Biosearch 558 Technology, they were labelled with either Atto-550, CalFluor-610 or AlexaFluor-647. 559 Each gene specific probe mix was labelled by mixing 2μl of the gene-specific X-560 FLAP probe mix (100μM), 2.5μl of fluo-FLAP (100μM) and 5μl of 10x NEB buffer 3 in 561 a final volume of 50μl. The hybridisation cycle was 85°C 3 min, 65°C 3 min and 562 25°C 3 min. The labelled probe was stored at -20°C. 563

Whole mount smiFISH 564
Whole-mount smiFISH protocol for zebrafish embryos was developed by adapting 565 smiFISH protocol from (Marra et al., 2019). Embryos were fixed in 4% formaldehyde 566 in 1x PBS. After smiFISH protocol, embryos were stained with Phalloidin-Alexa Fluor 567 488 (400x dilution in PBS 1x-Tween 0.1%) for 1h at room temperature and followed 568 by 3 washes with PBS-Tween. Embryos were embedded in 4% low melting point 569 agarose (Sigma) to collect 250μm thickness hindbrain transversal sections. 570 smiFISH microscopy and deconvolution 571 smiFISH images were collected using Leica TCS SP8 upright confocal with HC APO 572 L U-V-I 63x/0.9 water lens, magnification 0.75x. We acquired three-dimensional 573 stacks 1024 x 1024 pixels and z size 0.63μm. magnification 0.75x. Bits Per Pixel: 16. 574 Pinhole: 1 Airy Unit. Scan speed: 200. Channels were sequentially imaged. smiFISH 575 images were collected with frame accuracy 3 and line average 6. 576 Deconvolution of confocal images was performed using Huygens Professional Soft-577 ware. As pre-processing steps, the images were adjusted for (1) 'Microscopic Pa-578 rameters' and for (2) 'object stabilizer' as additional restoration, the latter was used 579 to adjust for any drift during imaging. Following, we used the deconvolution Wizard 580 tool, the two main factors to adjust during deconvolution were the background values 581 and the signal to noise ratio. Background was manually measured for every image 582 and channel, while the optimal signal to noise ratio identified for the images was 583 value 3. After deconvolution the images were generated using Imaris 9.5. 584

smiFISH segmentation 585
Segmentation was performed using Phalloidin-AlexaFluor 488 as membrane marker. 586 Using imaris 9.5 software we selected the 'Cells tool' from which 'Cells only' was used as detection type and 'Cell boundary' was selected as cell detection type. 588 Automated segmentation was performed followed by manual curation to identify for 589

cells incorrectly segmented. 590
To quantify pri-mir-9 nascent transcriptional sites we used the 'Spot tool'. The esti-591 mated spot diameter size was XY 1μm and Z 2μm. We used the default parameters 592 to identify the nascent transcriptional sites and further manual curation was per-593 formed to correct for minimal errors carried out by the software. Further on, spots 594 were imported into the segmented cells to identify the cells that contained one, two 595 or three pri-mir-9s. 596