Unified bursting strategies in ectopic and endogenous even-skipped expression patterns

Transcription often occurs in bursts as gene promoters switch stochastically between active and inactive states. Enhancers can dictate transcriptional activity in animal development through the modulation of burst frequency, duration, or amplitude. Previous studies observed that different enhancers can achieve a wide range of transcriptional outputs through the same strategies of bursting control. For example, despite responding to different transcription factors, all even-skipped enhancers increase transcription by upregulating burst frequency and amplitude while burst duration remains largely constant. These shared bursting strategies suggest that a unified molecular mechanism constraints how enhancers modulate transcriptional output. Alternatively, different enhancers could have converged on the same bursting control strategy because of natural selection favoring one of these particular strategies. To distinguish between these two scenarios, we compared transcriptional bursting between endogenous and ectopic gene expression patterns. Because enhancers act under different regulatory inputs in ectopic patterns, dissimilar bursting control strategies between endogenous and ectopic patterns would suggest that enhancers adapted their bursting strategies to their trans-regulatory environment. Here, we generated ectopic even-skipped transcription patterns in fruit fly embryos and discovered that bursting strategies remain consistent in endogenous and ectopic even-skipped expression. These results provide evidence for a unified molecular mechanism shaping even-skipped bursting strategies and serve as a starting point to uncover the realm of strategies employed by other enhancers.


Introduction
In animal development, enhancers, cis-regulatory elements that can act at a distance to modulate the transcription of genes (Banerji et al., 1981(Banerji et al., , 1983Gillies et al., 1983) orchestrate the formation of gene expression patterns that dictate animal body plans (Davidson, 2010;Franks, 1991;Lewis, 1978). At the single-cell level, transcription of most genes has been shown to occur in stochastic pulses, or bursts, of mRNA synthesis (Dar et al., 2012;Golding et al., 2005;McKnight & Miller, 1979;Raj et al., 2006;Senecal et al., 2014;Skupsky et al., 2010;Zenklusen et al., 2008), and patterned developmental genes are no exception (Berrocal et al., 2020;Bothma et al., 2014;Fukaya et al., 2016;Lammers et al., 2020;Zoller et al., 2018). Enhancers typically feature binding sites for several transcription factors proteins. Through these binding sites, enhancers can read out transcription factor concentration and modulate transcriptional bursting dynamics of the genes they regulate (Bothma et al., 2014(Bothma et al., , 2015Chen et al., 2018;Fukaya et al., 2016;Small et al., 1992;Yuh et al., 1994). Transcriptional bursting can be described by the two-state model of promoter activity (Lionnet & Singer, 2012;Peccoud & Ycart, 1995;Sanchez et al., 2013) that depicts bursts as the result of a gene promoter that switches stochastically between an inactive state, OFF, and an active state, ON, at a rate k on . When the promoter is in its ON state, it loads RNA Pol II molecules onto the gene at a rate r until, eventually, the promoter transitions back to the OFF state at a rate k off and mRNA synthesis stops (Figures 1A and 1B). In this model, there are multiple distinct ways that enhancers could modulate the rate of mRNA production by tuning transcriptional parameters. For instance, enhancers could upregulate transcription through an increase in burst frequency (k on , also defined as a decrease in the interval between bursts or k on -1 ), burst duration (k off -1 study employing single-molecule mRNA FISH suggested that the transcriptional control of various D. melanogaster gap genes is characterized by the shared modulation of burst frequency and duration, while burst amplitude remains constant . These two examples suggest a surprising degree of unity-but also of diversity-in the way different enhancers interact with promoters to control transcriptional bursting.
Apparent regulatory unity between various enhancers could be the result of evolutionary adaptation of enhancers to the trans-regulatory inputs that they experience in their endogenous regions of activity. Under this model, we would expect to observe unified bursting strategies at endogenous regions of enhancer activity, while enhancers exposed to non-endogenous regulatory inputs could exhibit different bursting strategies than those observed within their canonical domains of activity. Alternatively, unified strategies of bursting control could result from constraints determined by the biochemistry of the transcriptional processes at enhancers and promoters. In this model, enhancers would control the same set of bursting parameters regardless of the identity and concentration of the input transcription factors at concentrations that enhancers have not encountered during their evolution.
To probe these two models in the context of D. melanogaster development, we used the eve gene as a case study. Specifically, we disrupted two of its enhancers to expand the transcriptional activity of the eve gene onto ectopic regions where enhancers dictate transcriptional bursting in the presence of combinations and concentrations of input transcription factors that D. melanogaster eve enhancers have not encountered in their evolution. We compared bursting parameters in endogenous ( Figure 1C) and ectopic regions of eve expression ( Figure 1D) and determined that, despite endogenous regions having a higher mean transcriptional output than ectopic regions of eve expression, nuclei in endogenous and ectopic regions modulate their transcriptional output through the same bursting strategies: a concerted increase in promoter k on and r, while k off remains largely unchanged. Our results suggest that eve enhancers have not adapted to yield particular bursting parameters within eve stripes and add further evidence for a unified molecular mechanism behind the modulation of eve transcriptional output. Our work serves as a starting point for uncovering the realm of possible bursting strategies employed by enhancers and opens new research avenues to investigate how these strategies are established at the molecular level. According to the two-state model of promoter activity a gene promoter switches from the OFF (inactive) state to the ON (active) state at a rate k on . When ON, the promoter loads RNA Pol II molecules and synthesizes mRNA at a rate r. The promoter stochastically switches back to the OFF state at a rate k off . (B) The k on , k off , and r parameters define the average interval between bursts, average burst duration, and average burst amplitude, respectively. (C) eve stripes result from the interplay of various activators and repressors, for instance, wild-type eve stripe 2 is expressed through the interplay of the activators Bicoid and Hunchback with the repressors Giant and Krüppel. The latter define the anterior and posterior boundaries of eve stripe 2, respectively. (D) Here, we coupled the disruption of the eve stripe 1 enhancer with the disruption of the anterior repression of eve stripe 2 exerted by the gap repressor Giant to drive ectopic eve expression anteriorly and compare bursting parameters between endogenous and ectopic expression patterns. Figures 1C and 1D are based on (Levine, 2013) and (Peel et al., 2005).

Results
Mutating eve enhancers to generate ectopic expression patterns We sought to determine whether eve enhancers regulate transcription by modulating the same set of bursting parameters in endogenous and ectopic eve expression regions. Specifically, we aimed to compare how eve enhancers drive transcriptional bursting in and out of the well-known seven endogenous eve stripes (Frasch & Levine, 1987;Hare et al., 2008).
As our starting point, we took a previously established BAC-based eve-MS2 reporter system (Berrocal et al., 2020) that carries a~20 kb DNA fragment around the D. melanogaster eve coding region containing the five eve enhancers responsible for regulating the expression of the seven eve stripes, other cis-regulatory elements such as neuronal and muscular regulatory elements (Fujioka et al., 1999(Fujioka et al., , 2013) that might influence eve stripe expression in early development (Fujioka et al., 1999(Fujioka et al., , 2013, and the late element (LE) that upregulates eve expression in all stripes in response to the EVE protein (Fujioka et al., 1996;Jiang et al., 1991) (Figure 2A). We will refer to this construct as eveMS2-BAC (see SI section: DNA constructs and fly lines in Materials and Methods). The MS2 reporter system fluorescently labels nascent mRNA molecules resulting in sites of nascent transcription appearing as puncta whose fluorescence is proportional to the number of active RNA Pol II molecules. As a result, the system allows for the visualization of transcriptional bursting at single locus resolution, in real-time, in living embryos (Chubb et al., 2006;Ferguson & Larson, 2013;Garcia et al., 2013;Golding et al., 2005;Golding & Cox, 2004). When inserted into the D.
To establish an ectopic eve expression pattern, we modified the eve reporter locus ( Figure 2A) (Berrocal et al., 2020). Specifically, we aimed to create an anterior expansion of eve stripe 2 beyond its endogenous expression domain and into ectopic regions where we could study transcriptional bursting under inputs foreign to an eve enhancer, e.g., higher levels of the activator Bicoid and the repressor Giant (Gt) ( Figure   1D). To make this possible, we leveraged the fact that the anterior boundary of eve stripe 2 is established through repression by Giant (Small et al., 1992). Classic work by Small et al. identified a minimal regulatory element of the eve stripe 2 enhancer (eveS2-MRE; Figure 2A) and found that deleting three Giant binding sites within this minimal enhancer produced a strong anterior expansion of eve stripe 2 in the context of a reporter driven by eveS2-MRE (Small et al., 1992).
We generated an eveMS2-BAC variant, where the three binding sites for Giant identified in the eveS2-MRE were disrupted on the complete eve stripe 2 enhancer (eveS1wt-eveS2Gt -) (Figure 2A and 2C). Live imaging experiments on eveS1wt-eveS2Gtembryos showed only transient ectopic expression at the inter-stripe region between eve stripes 1 and 2. This transient inter-stripe expression lasts until 30-35 min into nc14; while inter-stripe expression between eve stripe 1 and eve stripe 2 disappears after~20 min in wild-type embryos (compare Figure 2B and 2C; compare Supplemental Figure 1A and 1B). These eveS1wt-eveS2Gtembryos did not produce the robust anterior expansion of eve stripe 2 described for the eveS2-MRE alone (Small et al., 1992). We attribute this muted anterior expansion in eveS1wt-eveS2Gtembryos ( Figure 2C) to the regulatory sequences not present in the original minimal eve stripe 2 reporter construct which might provide a buffering effect to the disruption of the three Giant binding sites (Lopez-Rivera et al., 2020).
In an attempt to expand the anterior ectopic domain of eveS1wt-eveS2Gt -, we sought to free its expression domain from any potential interference from eve stripe 1 expression.
To make this possible, we deleted endogenous expression corresponding to the eve stripe 1 enhancer. Specifically, we generated a mutant version of eveMS2-BAC with the eve stripe 1 enhancer deleted (eveS1∆-eveS2wt) (Figure 2A and 2D; Supplemental Figure 1C). Unexpectedly, these embryos still exhibited a dim eve stripe 1 (~30% of embryo length) after~30 min into nc14, perhaps due to the activity of the eve late element; and a dim additional anterior stripe that we refer to as eve stripe 0 (~20% embryo length) after~25 min into nc14. The appearance of eve stripe 0 implies a repressive role of eve stripe 1 enhancer beyond the anterior boundary of eve stripe 1 ( Figure 2D).
Finally, we coupled the three deletions of Gt-binding sites in the eve stripe 2 enhancer from eveS1wt-eveS2Gtwith the complete deletion of the eve stripe 1 enhancer in eveS1∆-eveS2wt to create eveS1∆-eveS2Gt - (Figure 2A and 2E; Supplemental Figure   1D). Surprisingly, eveS1∆-eveS2Gtembryos revealed large ectopic regions of eve expression more complex than the sum of patterns displayed by the independent mutants described above. Beyond a stronger and longer-lasting inter-stripe expression between eve stripe 1 and eve stripe 2 than observed in eveS1wt-eveS2Gt -, eveS1∆-eveS2Gtembryos exhibited the following notable features: a stronger-than-wild-type eve stripe 2 (located at~40% of embryo length); the presence of eve stripe 1 (~30% of embryo length) and eve stripe 0 (~20% embryo length); and many eve-active nuclei in normally silent inter-stripe regions between eve stripe 2 and eve stripe 0 ( Figure 2E). The fact that the knock-out of eve stripe 1 enhancer coupled with the disruption of Gt-binding sites in eve stripe 2 enhancer renders more ectopic expression on the anterior half of fruit fly embryos than the independent disruptions in eveS1∆-eveS2wt and eveS1wt-eveS2Gtimplies that the repressive activity of the eve stripe 1 enhancer synergizes with the repression that Giant exerts over the eve stripe 2 enhancer.
Taken together, our results suggest that the eve stripe 1 enhancer has a repressing role in the anterior half of fruit fly embryos that synergizes with the Giant repressor bound to the eve stripe 2 enhancer. This argues in favor of some kind of cross-activity between the eve stripe 1 and 2 enhancers that impacts eve expression in the anterior half of the embryo. eve stripe 1 enhancer might be also playing a role in the regulation of eve stripe 2, as Giant-binding site deletions in eve stripe 2 enhancer alone do not result in the stronger-than-wild-type eve stripe 2 observed in eveS1∆-eveS2Gtembryos. In summary, coupling the disruption of Giant-binding sites in eve stripe 2 enhancer with the deletion of eve stripe 1 enhancer produces different mutant patterns than the sum of the individual mutants. Finally, regardless of the complex regulatory interactions uncovered by our enhancer mutants, our results indicate that the ectopic gene expression patterns driven by our eveS1∆-eveS2Gtreporter provide an ideal scaffold for our investigations of the regulation of transcriptional bursting outside of endogenous embryo regions. Boxes represent enhancers (e.g., eve stripe 2 enhancer is labeled as 2). LE is the eve late element. eveMS2-BAC is a reporter of wild-type eve expression. The eveS1wt-eveS2Gtcarries a deletion of three Giant binding sites within the eve stripe 2 minimal regulatory element (eveS2-MRE; (Small et al., 1992)), as indicated by the three red crosses over the stripe 2 enhancer, and as shown in the detail of eveS2-MRE; where triangles represent transcription factor-binding sites. The eveS1∆-eveS2wt carries a deletion of the stripe 1 enhancer. Finally, eveS1∆-eveS2Gtcombines the Giant binding site deletions from eveS1wt-eveS2Gtwith the stripe 1 enhancer deletion of eveS1∆-eveS2wt. (B) Left. Stills from a representative wild-type embryo at~25 min and~45 min into nuclear cycle 14 (nc14). Nuclei are labeled in red and transcription sites are labeled in green. Right. Kymograph of eve expression averaged over 5 eveMS2-BAC (wild-type) embryos. Time resolution along the y-axis is 20 seconds. The position of nuclei along the x-axis was calculated from various datasets, based on the inferred position of stripe centers, as described in the SI section: Generation of heatmaps in Figure 2 and Supplemental Figure 1 in Materials and Methods. MS2 fluorescence in arbitrary units (AU) along the x-axis was averaged from nuclei located within bins of 0.5% embryo length. (C) Left. eveS1wt-eveS2Gtembryo at~25 min and~45 min into nc14. Right. Average eve-MS2 fluorescence from 6 eveS1wt-eveS2Gtembryos. At~25 min, some transcriptionally active nuclei in the inter-stripe region between eve stripe 1 and eve stripe 2 can still be detected (white arrows), while, in wild-type embryos, eve stripe 1 and 2 are completely separated by~20 min into nc14. (D) Left. eveS1∆-eveS2wt embryo at 25 min and~45 min into nc14. Right. Average eve-MS2 fluorescence from 5 eveS1∆-eveS2wt embryos. eve stripe 1 is almost absent at~25 min, but appears later, probably driven by activity of the eve late element. A dim eve stripe 0 is apparent (white arrows). (E) Left. eveS1∆-eveS2Gtembryo at~25 min and 45 min into nc14. Right. Average eve-MS2 fluorescence from 6 eveS1∆-eveS2Gtembryos. At~25 min, there is a strong ectopic expression in the inter-stripe region between eve stripe 1 and eve stripe 2 (white arrow). At~45 min, this ectopic inter-stripe expression has dimmed (white arrows), while eve stripe 0 becomes apparent.

Bursting strategies are uniform across endogenous and ectopic eve-active nuclei
We determined the position of nuclei displaying active eve transcription and labeled them as endogenous if they were positioned within the boundaries of wild-type eve stripes (eve stripe 1, eve stripe 2, eve stripe 3, eve stripe 4); or as ectopic if they were located in the inter-stripe region between eve stripe 1 and eve stripe 2 (eve stripe 1-2) or in eve stripe 0 (in the far anterior) ( Figure 3A) as described in Materials and Methods.
eve stripe 1 expression in embryos with disrupted eve stripe 1 enhancer was considered endogenous, as we believe that this expression results from activity of the late element. All active nuclei in wild-type embryos were labeled as endogenous.
Overall, ectopic regions show lower levels of mean MS2 fluorescence than endogenous regions, as is evident by comparing eve the interstripe 1-2 and eve stripe 0 against eve stripe 1, eve stripe 2, and eve stripe 3 in eveS1∆-eveS2Gtembryos ( Figure 2E, Right). This is perhaps due to the unavailability of optimal concentrations of transcription factors; e.g. a lack of activators or an excess of repressors with respect to the concentrations found in endogenous regions ( Figure 1C and 1D).
To uncover which bursting parameters are modulated to create each endogenous and ectopic stripes and interstripe regions, we need to extract the bursting parameters in each region. We computed bursting parameters for nuclei grouped by stripe and binned by transcriptional output (Supplemental Figure 2) in our four fly lines, with the following rationale. In the bursting model, the average rate of transcription initiation is described by the formula , where indicates the fraction of time the promoter + + spends in the ON state . As enhancers and their inputs (e.g. transcription factors, chromatin state) define bursting parameters (k on , k off , r), nuclei of similar average transcriptional output within the same stripe should be driven by similar inputs acting over the same enhancer. Thus, these nuclei should show similar values of the bursting parameters k on , k off and r that satisfy the equation above. On the other hand, our model predicts that nuclei with different fluorescence must differ in at least one of their bursting parameter values (k on , k off and/or r).
The average MS2 fluorescence is a direct reporter of the average rate of transcriptional initiation. Single-cell MS2 fluorescence measurements reflect the transcriptional dynamics of individual promoters as they undergo transcriptional bursting ( Figure 3B).
However, the actual promoter states, or bursting parameters, underlying the transcriptional bursting remain 'hidden', as RNA Pol II molecules engage in elongation for several minutes (~140 sec for the MS2::yellow transcriptional unit in our reporter system) (Berrocal et al., 2020). As a result, MS2 fluorescence is observable even after the promoter switches to the OFF state, convolving the promoter switching dynamics with those of transcriptional elongation. Thus, we can only compute promoter states by inferring them from MS2 fluorescence over time. To infer hidden promoter states, we used a compound-state Hidden Markov Model (cpHMM) developed by . By inferring the succession of activity states, cpHMM estimates rates of transitioning between the OFF and ON states (k on and k off ) and the rate at which ON promoters load active RNA Pol II molecules (r).
Consistent with our previous work (Berrocal et al., 2020), we find that endogenous stripes in eveMS2-BAC wild-type embryos modulate their transcriptional output (mean MS2 fluorescence in wild-type embryos ranges from 2 to 15 AU) by tuning the average k on (from 0.5 to 1.5 OFF to ON promoter transitions per minute) and r (from an average fluorescence increase at a rate of 5 AU per minute to 10 AU per minute). The average k off value remains largely constant (0.5 ON to OFF promoter transitions per minute), with only a minor downregulation at high transcription outputs ( Figure 3C). Thus, we confirm that eve-active nuclei in all wild-type stripes achieve higher levels of transcription by upregulating average bursting frequency (k on ) and amplitude (r), while average burst ) remains largely the same.
eveS1wt-eveS2Gt -( Figure 3D) and eveS1∆-eveS2wt ( Figure 3E) embryos did not yield enough ectopic nuclei for cpHMM inference. However, their endogenous stripes followed the same bursting strategy observed in wild-type embryos, regardless of whether stripes were activated by wild-type or mutant enhancers (see SI Section: Complementary Analysis of Bursting Parameters in Materials and Methods). We inferred bursting parameters across regions of endogenous and ectopic nuclei in eveS1∆-eveS2Gtembryos (eve stripe 1-2 and eve stripe 0), as they yielded sufficient ectopic eve-active nuclei to support cpHMM inference. As noted previously, these embryos feature an eve stripe 2 with nuclei of higher transcriptional output than wild-type embryos (compare Figure 2B and 2E), and a large region of ectopic expression towards the embryo anterior. Despite these differences in transcriptional output, bursting parameters in endogenous and ectopic eve-active nuclei in eveS1∆-eveS2Gtembryos follow the same trends as wild-type embryos (Supplemental Figure 3). In all regions-both endogenous and ectopic-enhancers increase transcription by increasing in k on and r, while k off remains largely constant ( Figure 3F).
We performed an orthogonal cpHMM inference of bursting parameters by grouping nuclei in only two categories (endogenous and ectopic) (Supplemental Figure 4)  Only eve stripe 0, 1, 1-2, and 2 are shown for clarity. Supplemental Figure 3 includes eve stripe 3, and 4. (B) MS2 fluorescent traces (green) and fit using the cpHMM model (black) from embryos of different genotypes. Transcription in Drosophila embryos occurs after DNA replication. Since replicated sister chromatids remain paired, each eve locus contains two promoters, and every one of them can be ON or OFF. Purple bars show cpHMM-inferred promoter state corresponding to the two sister chromatids within a transcription spot . Absence of bars represents both sister promoters OFF; shorter bars represent 1 sister promoter ON; longer bars represent 2 sister promoters ON. We aggregated the active state of 1 and 2 sister promoters into a single ON state, which leads to an effective two-state model of promoter activity (see SI section: Inference of Bursting Parameters in Materials and Methods). Each point in the plots below was computed from~40 fluorescent traces. (C) As previously observed in eve-MS2 wild-type embryos (Berrocal et al., 2020), nuclei in all stripes follow the same trends in bursting parameters. k on , the average rate at which the promoter switches from OFF to ON increases with increasing transcriptional initiation as reported by MS2 fluorescence. k off , the average rate at which a promoter switches from ON to OFF remains largely constant, and has a slight decrease in nuclei with the highest MS2 fluorescence values. r, the average rate at which active promoters increase their fluorescence, is higher in brighter nuclei. All stripes from (D) eveS1wt-eveS2Gtand (E) eveS1∆-eveS2wt share the same bursting strategy. (F) The same trends occur in endogenous (eveS1 and eveS2; solid lines) and ectopic stripes (eveS0 and eveS1-2; dotted lines) of eveS1∆-eveS2Gtembryos.

Discussion
Over the last few years the ability to infer bursting parameters from fixed (Little et al., 2013;Xu et al., 2015) and live-imaging  data in embryos has revealed several commonalities and differences in the strategies employed by different enhancers to modulate bursting parameters and create patterns of gene expression (Berrocal et al., 2020;Zoller et al., 2018). Indeed,  observed that Drosophila gap genes, controlled by independent promoters and enhancers, modulate bursting through a common strategy; an increase in frequency and duration, while burst amplitude remains unchanged.
These findings hint at an opportunity to classify enhancers and promoters in families whose members employ the same strategy of bursting control and rely on a common molecular mechanism to regulate their target genes.
In the light of our results, two molecular mechanisms coupled to enhancer activity could be behind the unified bursting strategies of eve enhancers. First, the observed common modulation of bursting parameters might result from general constraints imposed by the transcriptional machinery at enhancers or promoters. Previous work showed that topological dynamics of bacterial chromosomes brought by transcriptional activity shape bursting in bacteria (Chong et al., 2014); while histone acetylation of the circadian promoter Bmal1 modulates burst frequency in mammalian cells (Nicolas et al., 2018).
Furthermore, (Gorski et al., 2008) observed that the dynamics of RNA Pol I-subunit assembly affect transcriptional output. The dynamic nature of transcription factor "hubs" (Mir et al., 2017;Tsai et al., 2017) in transcriptionally active enhancers of D.melanogaster embryos (Mir et al., 2018) may impact transcriptional bursting as well.
The second possibility is that the eve promoter, which is shared by all eve enhancers and distant regulatory elements, constrains the regulatory strategy of even-skipped.
Recent studies using MS2 live imaging ( Both possibilities suggest that a molecular mechanism coupled to eve transcription restricts the landscape of bursting strategies available to eve enhancers. Our results indicate that eve bursting strategies are a fundamental property of enhancers and promoters-and not the result of changing trans-regulatory environments-and show that eve enhancers merely act as knobs, robust to mutations, that tune transcriptional output levels by modulating bursting through a largely fixed k off and shifting r and k on .
An ectopic pattern of particular interest is the novel eve stripe 0 brought by the deletion of the eve stripe 1 enhancer. This new stripe shows that mutations on existing eve enhancers can generate novel gene expression patterns through the same bursting strategies employed by the other eve stripes. Since expression patterns in embryonic development shape the formation and identity of animal body plans (Akam, 1983;Davidson, 2010;Lewis, 1978), the appearance of new expression patterns may constitute a critical driver of evolution (Rebeiz et al., 2011). Figure 2 (

Supplemental Figure 2: Pipeline for the quantification of eve bursting parameters (k on , k off , r) in nuclei grouped by stripe and binned by mean MS2 fluorescence (Figure 3). (A)
Nuclei in embryos of the same genotype were assigned to a stripe as described in the main text. Here, as an illustrative example, we will follow the analysis of inter stripe 1-2 (vermillion) and eve stripe 2 (yellow) in eveS1∆-eveS2Gtembryos. (B) Nuclei in eve interstripe 1-2 were sorted in three bins of 46-50 nuclei and 2800 data points according to their mean MS2 fluorescence (4. 05,9.68,and 16.22 AU). Nuclei in eve stripe 2 were sorted in six bins of 39-58 nuclei and~2700 data points according to their mean MS2 fluorescence (5. 01,9.97,14.62,17.95,21.67,and 26.11 AU). Bursting parameters (k on , k off , and r) were calculated for each bin using the cpHMM by . This analysis was performed with data from six eveS1∆-eveS2Gtembryos. (C) Our analysis makes it possible to plot bursting parameters (y-axis) against mean MS2 fluorescence (x-axis) of each bin.

Bursting parameters in endogenous stripes controlled by mutant enhancers
Some stripes in this work are driven by mutant eve enhancers. We found that mutated enhancers modulate transcriptional output of endogenous stripes through the same mechanism as their wild-type counterparts: an increase in k on and r, while k off remains largely constant (Supplemental Figure 3). In eveS1wt-eveS2Gtembryos (Supplemental Figure 3C), eve stripe 2 is driven by a mutant eve stripe 2 enhancer. In eveS1∆-eveS2wt embryos (Supplemental Figure 3D), eve stripe 1 is active in the absence of eve stripe 1 enhancer, perhaps due to the activity of the late element. In eveS1∆-eveS2Gtembryos (Supplemental Figure 3E), eve stripe 2 is driven by a mutant eve stripe 2 enhancer and eve stripe 1 is active in the absence of eve stripe 1 enhancer.
In all cases, our findings support the hypothesis that eve-regulatory elements employ a unified strategy to modulate transcriptional output. Bursting parameters of eve stripe 1 in embryos with a deleted eve stripe 1 enhancer (eveS1∆-eveS2wt; eveS1∆-eveS2Gt -) are of particular interest, as this expression is most likely activated by the eve late element. If this is the case, the eve late element would modulate transcriptional output through the same mechanism as the other enhancers, further underlining the unity of regulatory strategies across different eve-regulatory elements.

Comparison of bursting parameters between sets of nuclei grouped in endogenous and ectopic categories
We computed the bursting parameters of 3-6 bins per stripe (Supplemental Table 2), depending on the amount of data obtained (see SI: Supplemental Figure 2 and Inference of Bursting Parameters in Materials and Methods). To rule out the possibility that the observed k on , k off , and r trends were skewed by the small number of bins, we aimed to redo our analysis with more data points per category (endogenous and ectopic), as a way to contrast bursting parameters between whole endogenous and ectopic regions and examine the bursting parameters trends that result from having 6-13 bins per category (Supplemental Table 3).
We pooled together all nuclei from eveS1∆-eveS2Gtembryos into endogenous (eve stripe 1, eve stripe 2, eve stripe 3, eve stripe 4) and ectopic sets (eve stripe 0, eve inter-stripe 1-2), and binned them by their mean MS2 fluorescence output to infer and compare their bursting parameters. We did the same analysis in wild-type, eveS1wt-eveS2Gt -, and eveS1∆-eveS2wt embryos. We contrasted the bursting parameters of ectopic nuclei from eveS1∆-eveS2Gtembryos against sets of endogenous nuclei from eveS1∆-eveS2Gt -eveS1wt-eveS2Gt -, eveS1∆-eveS2wt, and wild-type embryos (Supplemental Figure 4) and observed that all of them follow the same bursting strategy. Ectopic nuclei from eveS1∆-eveS2Gtembryos boost transcriptional output through an increase in average k on (Supplemental Figure 4B) and r (Supplemental Figure 4D), while k off remains largely the same, with only a minor drop at high mean MS2 fluorescence values (Supplemental Figure 4C). The bursting parameters of endogenous nuclei from all the genotypes in this work follow the same trend.

Supplemental Figure 3. Bursting parameter inference for all stripes captured by our data.
We followed the analysis pipeline described in Supplemental Figure 2. k on (left panels), k off ,(middle panels) and r (right panels) trends are similar in all endogenous and ectopic stripes in our dataset. (A) Position and color code of endogenous and ectopic stripes on a fruit fly embryo. (B) As previously observed in eve-MS2 wild-type embryos (Berrocal et al., 2020), nuclei in all stripes follow the same trends in bursting parameters. All stripes in wild-type embryos are endogenous and are controlled by wild-type enhancers. (C) The same trend is observed in all endogenous stripes from eveS1wt-eveS2Gt -, regardless of whether they are controlled by wild-type enhancers (eveS1, eveS3, eveS4); or by mutant enhancers (eveS2). (D) endogenous stripes from eveS1∆-eveS2wt embryos controlled by wild-type (eveS2, eveS3, eveS4) and mutant (eveS1) enhancers display the same trend. (E) All endogenous stripes controlled by wild-type (eveS3, eveS4) and mutant (eveS1, eveS2) enhancers, and ectopic stripes (eveS0, eveS1-2) from eveS1∆-eveS2Gtembryos share the same bursting strategy.

Supplemental Figure 4: Comparison of bursting parameters between endogenous and ectopic gene expression regions.
We followed the cpHMM-based analysis pipeline (as described in Supplemental Figure 2) on nuclei grouped in two categories: endogenous (eveS1, eveS2, eveS3, and eveS4) and ectopic (eveS0 and eveS1-2); instead of grouping nuclei by stripes.k on , k off , and r parameters of ectopic (red) and endogenous (black) regions, estimated from nuclei binned by their mean MS2 fluorescence. Ectopic regions (red solid line) from eveS1∆-eveS2Gtembryos follow the same bursting strategies as the endogenous regions from all other genotypes: wild-type (black dash-dot line), eveS1∆-eveS2Gt -(black solid line), eveS1wt-eveS2Gt -(black dashed line), eveS1∆-eveS2wt (black

DNA constructs and fly lines
We generated 4 reporter constructs based on a previously established Bacterial Artificial Chromosome (BAC) carrying the~20 Kb DNA sequence around eve (Venken et al., 2006(Venken et al., , 2009, and whose eve coding sequence has been replaced by an MS2::yellow transcriptional unit (Berrocal et al., 2020). We used wild-type eveMS2-BAC from (Berrocal et al., 2020). The other 3 BAC constructs were derived from wild-type eveMS2-BAC. These constructs carried mutant versions of eve stripe 1 and eve stripe 2 enhancers. Vector Builder (https://en.vectorbuilder.com/) generated the mutant versions through ccdB-amp cassette mediated recombineering. These mutant BACs are available on Vector Builder's website. SnapGene (.dna) files with eveMS2 BAC sequences are in the repository https://github.com/aberrocal/BurstingStrategies-eve.git, folder BurstingStrategies-eve/_DataSubmission/BACSequences/. eveS1wt-eveS2Gt -BAC construct (Vector Builder-Service Proposal: P180328-1009dgs) contains a wild-type eve stripe 1 and a mutant version of eve stripe 2 enhancer with three Giant-binding sites deleted, as shown in Table I of (Small et al., 1992). We chose to disrupt the three Gt-binding sites within the eve stripe 2 enhancer ( Figure 2B) that had previously been tied to ectopic anterior expansion of eve stripe 2 expression when deleted in the context of the Minimal Regulatory Element of the eveS2 enhancer (eveS2-MRE) (Small et al., 1992). eveS2-MRE is a 480bp regulatory sequence within the eve stripe 2 enhancer (~2kb total length) sufficient to drive the expression of eve stripe 2.
eveS1∆-eveS2Gt -BAC construct (Vector Builder-Service Proposal: P180614-1002pzr) has the eve stripe 1 enhancer, as defined by ChIP-seq data of the enhancer-associated protein Zelda (Harrison et al., 2011), replaced by a ccdB-amp cassette and eve stripe 2 enhancer replaced by a mutant version with three Giant binding sites deleted as described above.
eveS1∆-eveS2wt BAC construct (Vector Builder-Service Proposal: P190605-1001zkt) has eve stripe 1 enhancer replaced with a ccdB-amp cassette and a wild-type eve stripe 2. To sum up, we used the fly line carrying wild-type eveMS2-BAC from (Berrocal et al., 2020) and we generated 3 new fly lines carrying genome integrations of the aforementioned constructs. The mutant versions of eveMS2-BAC used in this work were inserted in the genome via ϕC31 integrase mediated recombination. Mutant constructs were either sent to BestGene Inc (eveS1wt-eveS2Gt -, eveS1∆-eveS2wt) for germline injection or injected in our laboratory (eveS1∆-eveS2Gt -). All constructs integrated into a ϕC31 AttP insertion site in chromosome 3L (Bloomington stock

Imaging
We crossed male flies from lines carrying eveMS2-BAC constructs (w-; +; MS2::yellow) and female flies carrying His::RFP and MCP::GFP fusion proteins (yw; His::RFP; MCP::GFP) (Garcia et al., 2013). His::RFP allows for visualization of nuclei, MCP::GFP binds MS2 nascent transcripts to form fluorescent puncta at sites of nascent MS2 transcription. We set embryo-collection cages with~30 male and~100 female fruit flies, and collected offspring embryos after 1h 30min. All movies in the same dataset were recorded within~1 week. We mounted embryos on a slide for confocal imaging, as described in (Berrocal et al., 2020;Bothma et al., 2014). Aging embryos for 1h 30min allows us to capture the entire interval between the 14th synchronous cell cleavage and the beginning of gastrulation. We recorded a total of 22 live embryos as shown in Supplemental Table 1. All imaging was done in a Zeiss-800 scanning-laser confocal microscope. Movies of embryonic development were captured under a 63x oil objective, in windows of 202.8 µm x 50.7 µm, at pixel size of 0.2 µm, zoom 0.5x. Movies were recorded in two channels, EGFP for MS2 signal, and TagRFP for His::RFP signal.
Imaging parameters were 16 bits per pixel, scan mode frame, bidirectional scanning, scan speed 7, pixel dwelling 1.03 µsec, laser scanning averaging 2, averaging method mean, averaging mode line, laser power EGFP 30 µW and TagRFP 7.5 µW, master gain in EGFP channel 550V and in TagRFP channel 650V, digital offset in both channels 0, digital gain in both channels 1, pinhole size 44 µm (1 Airy unit -0.7 µm/section) at 63x objective, laser filters EGFP:SP545 and TagRFP:LBF640. Data points consist of Z-stacks of 21 slices separated by intervals of 0.5 µm, to span a range of 10 µm across the Z axis. Z-stack mode full stack. Whole Z-stacks were recorded every 16.8 sec (wild-type, eveS1wt-eveS2Gt -, eveS1∆-eveS2Gt -) and 19.5 sec (eveS1∆-eveS2wt). The difference in time resolution between datasets does not impact our analysis, as the cpHMM analyzes interpolated data points at 20 s intervals. These parameters are based on the imaging protocol and settings in (Berrocal et al., 2020). We stopped live imaging of individual embryos after 50 min into nuclear cycle 14, before the cell rearrangements of gastrulation, and took mid-sagittal and surface images of the whole embryo to localize our 202.8 µm x 50.7 µm window along the embryonic anterior-posterior axis. Raw data from confocal microscope imaging is publicly available Supplemental Table 1: Datasets and stripes. We recorded 5 wild-type eveMS2-BAC (eveS1wt-eveS2wt) datasets, 6 eveS1wt-eveS2Gt -(eveS1wt_eveS2Gt), 5 eveS1∆-eveS2wt (eveS1Null_eveS2wt), and 6 eveS1∆-eveS2Gt -(eveS1Null_eveS2Gt) for a total of 22 datasets. Movies in every dataset capture between 3 and 6 stripes. Supplemental Table 1 shows stripes captured in each dataset. Stripes in parentheses had few active nuclei (eveS0) or were not captured in their entirety (eveS4) and (eveS5). Asterisks indicate datasets used for stills in Figure 2.

Segmentation and quantification of movies
We tracked MS2 foci from movies and segmented them using the MATLAB based analysis pipeline developed by (Berrocal et al., 2020;Garcia et al., 2013;. Specifically, for segmentation of MS2/MCP::GFP foci across stacks on the Z-axis, we combined the MATLAB pipeline mentioned above with Fiji-Weka Segmentation 3D software, as described in (Berrocal et al., 2020). The

Assignment of eve-active nuclei to stripes
We manually segmented nuclei from eveS1∆-eveS2Gtand eveS1wt-eveS2Gtfly lines, as their stripes were not always clearly discernible. For these embryos, we assigned nuclei to individual stripes based on the position of stripes at 45 min into nc14, when they became separated from the background. The boundary between eve stripe 1-2 and eve stripe 2 in eveS1∆-eveS2Gtembryos was set at 36% of embryo length, according to the kymograph of MS2 fluorescence over time. On the other hand, eveS1∆-eveS2wt and wild-type embryos showed defined stripes after 25 min into nc14. Thus, we used a MATLAB k-means clustering algorithm to dynamically assign eve-active nuclei to individual stripes, tracking nuclei by the accumulation of MS2 fluorescent output in windows of five-minutes. Nuclei active between 0 and 25 min into nc14 were assigned to stripes based on their position at 25 min into nc14. We generated movies of segmented MS2 spots assigned to individual stripes in windows of~5 minutes. MATLAB scripts for manual and k-means-automated segmentation of stripes, as well as scripts to generate movies of segmented stripes are available in github (see Data and Code). Figure 2 and Supplemental Figure 1 We used traces of MS2 fluorescence intensity over time, which reflect transcriptional activity, to generate heatmap/kymographs of MS2 transcription datasets. We generated heatmaps ( Figure 2, Supplemental Figure 1) by collapsing data points from all embryos of the same genotype into a single kymograph plot. We started by adjusting the position of nuclei in each embryo relative to nuclei in other embryos of the same genotype. As we had assigned MS2 active nuclei to individual stripes, we measured the distance along the anterior-posterior axis from each MS2 focus to the center of its corresponding stripe. We inferred the position of pseudo-stripes formed by the combined data from all embryos of the same genotype. We calculated the position of pseudo-stripes along the anterior-posterior embryo axis by averaging the position of the center of stripes along the anterior-posterior axis in individual embryos of the same genotype. Finally, we assigned a position to all nuclei of the same genotype relative to pseudo-stripes by positioning them at the same distance from the center of pseudo-stripes as they were from the center of the stripe where they originated. We followed the same procedure to locate the position of inactive nuclei.

Labeling eve patterns as endogenous or ectopic
To compare the bursting parameters between endogenous and ectopic regions of eve activity, we segmented MS2-active nuclei and assigned them to individual regions that were deemed to be either endogenous or ectopic. We labeled regions as endogenous if their position overlapped within the boundaries of wild-type eve stripes (eve stripe 1, eve stripe 2, eve stripe 3, eve stripe 4); or as ectopic if their position overlapped with the inter-stripe region between eve stripe 1 and eve stripe 2 (eve stripe 1-2) or with the novel eve stripe 0 (~20% embryo length). All stripes in wild-type embryos were labeled as endogenous.

Inference of bursting parameters
We used a cpHMM approach, developed by  to extract average bursting parameters (k on , k off , r) from different sets of MS2-active nuclei. We input MS2 fluorescent traces over time from these sets into the cpHMM. Specifically, we combined nuclei from same-genotype embryos, sorted them by stripe and distributed them across bins of varying fluorescence. To ensure reliable inference, we enforced each bin to contain~40 nuclei, equivalent to~2500 time points at a 20 sec resolution . The number of bins was determined by the amount of data available (Supplemental Table 2).
Since transcription in Drosophila embryos occurs after DNA replication, and sister chromatids remain paired, each fluorescent spot in our data contains two promoters, each of which may be ON or OFF . To account for this, the cpHMM infers three states: OFF (both sister promoters inactive), ON 1 (one sister promoter active), and ON 2 (two sister promoters active). For ease of presentation, we aggregated ON 1 and ON 2 states into a single effective ON state. This leads to an effective two-state model with one OFF and one ON state and three burst parameters: k off -1 (the burst duration), k on (the burst frequency), and r (the burst amplitude). k on is defined as the sum of the transition rates from OFF to any of the two active states described above: OFF → ON 1 and OFF → ON 2 . k off is defined as the rate at which the system returns to the OFF state upon leaving it, which is described by the formula , where is the fraction of time the system spends in the OFF 1 state. k off is the inverse of mean burst duration (k off -1 ). r is defined by the average of the rates of transcription initiation in the two ON states (r 1 and r 2 ) weighted by the fraction of the time that the system spends on each state (p 1 and p 2 ) as described by the formula The output of cpHMM are bursting parameters (k on , k off , r) for each set of nuclei input into the model.Thus, Figure 3 and Supplemental Figure 3 are plots of mean k on , k off , r, and their standard deviations σ kon , σ koff , σ r , computed from sets of nuclei binned by stripe. For Supplemental Figure 4, we followed a similar approach, but grouping active nuclei by their endogenous or ectopic location. Nuclei grouped in endogenous and ectopic categories were distributed across 6-13 bins of increasing fluorescence (Supplemental Table 3). Their mean k on , k off , r, and standard deviations, σ kon , σ koff , σ r were plotted in Supplemental Figure 4.
Supplemental Table 2 Wild-type -Stripes Number of bins  Table 2: Binning by stripe. We pooled together nuclei from all embryos per dataset, sorted them by the stripe where they are located and distributed them in bins of varying fluorescence. Each bin contains~40 nuclei (~2500 time points). E.g., all nuclei in eve stripe 1 (eveS1) from the five eve wild-type embryos in our dataset were assigned to 3 bins according to their mean MS2 fluorescence, as each bin must contain ~40 nuclei, or ~2500 data points, for input into the cpHMM.
Supplemental Table 3 Wild-type Number of Bins Supplemental Table 3: Binning by endogenous/ectopic. We pooled together nuclei from all embryos per dataset, sorted them by endogenous or ectopic, according to whether the stripe where they were located was deemed endogenous or ectopic, and distributed them in bins of varying fluorescence. Each bin contains~40 nuclei (~2500 time points). E.g. All endogenous nuclei in the 5 eve wild-type embryos were distributed among 11 bins of increasing MS2 fluorescence. Some datasets have their ectopic bin empty, as they had less than ~40 active nuclei in their ectopic regions.