Author response: Optogenetic investigation of BMP target gene expression diversity
2020-08-12

Article Figures and data Abstract Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Signaling molecules activate distinct patterns of gene expression to coordinate embryogenesis, but how spatiotemporal expression diversity is generated is an open question. In zebrafish, a BMP signaling gradient patterns the dorsal-ventral axis. We systematically identified target genes responding to BMP and found that they have diverse spatiotemporal expression patterns. Transcriptional responses to optogenetically delivered high- and low-amplitude BMP signaling pulses indicate that spatiotemporal expression is not fully defined by different BMP signaling activation thresholds. Additionally, we observed negligible correlations between spatiotemporal expression and transcription kinetics for the majority of analyzed genes in response to BMP signaling pulses. In contrast, spatial differences between BMP target genes largely collapsed when FGF and Nodal signaling were inhibited. Our results suggest that, similar to other patterning systems, combinatorial signaling is likely to be a major driver of spatial diversity in BMP-dependent gene expression in zebrafish. Introduction Embryogenesis is orchestrated by signaling pathways that activate spatiotemporally diverse patterns of gene expression. A prominent theory relating signaling to gene expression diversity is the gradient threshold model, in which a signaling gradient across a tissue defines unique spatial gene expression domains by activating target genes at different signaling thresholds (Figure 1A; Sharpe, 2019; Briscoe and Small, 2015; Dubrulle et al., 2015; Rogers and Schier, 2011; Barkai and Shilo, 2009; Ashe and Briscoe, 2006). Gene expression patterns can also be influenced by signaling dynamics and expression kinetics (Sagner and Briscoe, 2017) as well as interactions with other signaling pathways (Briscoe and Small, 2015). However, in many patterning systems the factors leading to diverse developmental gene expression profiles are incompletely characterized. Here, we investigate how signaling levels, target gene expression kinetics, and combinatorial signaling contribute to gene expression diversity during dorsal-ventral patterning in zebrafish. Figure 1 with 1 supplement see all Download asset Open asset BMP target genes have diverse spatial expression patterns at shield stage. (A) The gradient threshold model states that a signaling gradient activates genes (blue, white, red) at different thresholds (dashed gray lines). (B) BMP binding induces receptor complex formation, phosphorylation of Smad1/5/9, and activation of target genes. (C) Schematic of shield-stage zebrafish embryos with BMP signaling gradients (magenta) along the dorsal-ventral axis. (D-E) Representative images (D) of pSmad1/5/9 immunofluorescence in embryos at the indicated time post-fertilization and quantification (E). (F-O’) Fluorescence in situ hybridization (FISH) showing spatial expression of the indicated high-confidence BMP target genes at shield stage (~6.75 h post-fertilization (hpf)). (F,G,H,I,J,K,L,M,N,O) are animal views, dorsal to the right. (F’,G’,H’,I’,J’,K’,L’,M’,N’,O’) are ventral views. Vertical white bars indicate regions where expression is excluded from the margin. (P-Y) Quantification of FISH signal along the dorsal-ventral axis for the indicated BMP target genes at shield stage (ventral on the left, dorsal on the right as in (E)). Normalized intensities are shown; error bars represent standard error. The Gaussian function Ae-x-μ2ς was fitted to each profile (gray lines), and gene expression range was defined as r=μ+2ς/2 (gray bars). Some BMP target genes could not be reliably quantified due to weak FISH signal (bmp4, id2a, smad6a, smad7, and znfl2b) or inability to reliably identify the ventral side in all assays (crabp2b). See the Figure 1—source data 1 file for source data. Figure 1—source data 1 Source data for Figure 1. https://cdn.elifesciences.org/articles/58641/elife-58641-fig1-data1-v2.xlsx Download elife-58641-fig1-data1-v2.xlsx We focused on patterning mediated by BMP, a TGF-β superfamily member with important developmental roles across the animal kingdom (reviewed in Zinski et al., 2018). BMP ligands bind and assemble complexes of type I and II receptor serine/threonine kinases, resulting in the phosphorylation of the signal transducers Smad1/5/9 and activation of BMP target genes (Figure 1B; Derynck and Budi, 2019). The regulation of BMP gradient formation during early development has been analyzed in a variety of organisms including Drosophila, Nematostella, and Xenopus (Genikhovich et al., 2015; Iber and Gaglia, 2007; Mizutani et al., 2005; Plouhinec et al., 2013) as well as zebrafish. During late blastula and early gastrulation stages in zebrafish embryos, graded transcription and subsequent diffusion of BMP ligands, together with dorsally secreted BMP inhibitors such as Chordin, generate a ventrally-peaking gradient of BMP signaling that patterns the dorsal-ventral axis (Figure 1C; Pomreinke et al., 2017; Zinski et al., 2017). Loss of BMP signaling results in dorsalization, whereas excess BMP signaling produces ventralized embryos (Zinski et al., 2018). The degree of dorsalization or ventralization can be modulated by mutations in BMP pathway components with different strengths (Mintzer et al., 2001; Barth et al., 1999; Nguyen et al., 1998; Mullins et al., 1996) or by injecting different amounts of mRNA encoding pathway activators or inhibitors (Schumacher et al., 2011; Dick et al., 2000; Kishimoto et al., 1997; Neave et al., 1997). These observations have led to the suggestion that BMP functions as a morphogen to pattern the dorsal-ventral axis by activating different target genes at different signaling level thresholds (Figure 1A; Zinski et al., 2018; Tuazon and Mullins, 2015; Schumacher et al., 2011; Barth et al., 1999; Nguyen et al., 1998; Neave et al., 1997; Mullins et al., 1996). However, overexpression and genetic manipulations can affect the duration of signal exposure, dysregulate other signaling pathways, and modify earlier aspects of development such as morphogenetic movements, complicating the interpretation of these experiments. Moreover, patterning of the dorsal-ventral axis by BMP and the germ layers by FGF and Nodal occurs simultaneously in zebrafish (Zinski et al., 2018), and although these pathways are known to interact, how FGF and Nodal influence the spatiotemporal expression of BMP target genes has not been systematically assessed. To identify the factors that contribute to differences in BMP target gene expression and rule out factors that do not contribute, we first identified BMP targets in early zebrafish embryos and quantified their diverse spatial (Figure 1) and temporal (Figure 2) expression patterns. We then used an optogenetic approach to generate acute BMP signaling pulses (Figure 3) and found that while most target genes can respond to early BMP signaling (Figure 4), differential transcription kinetics do not fully account for the observed expression differences (Figure 5). Further, target gene responses to high- and low-amplitude signaling pulses suggest that not all spatiotemporal target gene expression differences are due to different signaling activation thresholds (Figure 6). In contrast, inhibition of FGF and Nodal signaling homogenized the spatial expression patterns of BMP targets, suggesting that combinatorial regulation by BMP, FGF, and Nodal is a major driver of BMP target gene spatial diversity (Figure 7). Figure 2 Download asset Open asset BMP target genes have diverse temporal expression profiles. (A–N) Embryos were collected every 30 min from 2.75 to 7.25 hpf, and transcript levels were quantified using NanoString technology. Error bars represent standard error. Temporal profiles were fit with the cumulative distribution function of the normal distribution (gray lines), and activation time (arrowheads) was defined as the average time point at which the curves reached about two mean average deviations (i.e., 1.5∙τ) from the inflection point ν (excluding the maternally deposited genes id2a [Chong et al., 2005] and smad6a [White et al., 2017]). NanoString probes for two high-confidence activated BMP target genes (apoc1l and znfl2b) were not functional. (O) Average gene expression spatial range is plotted against average activation time. See the Figure 2—source data 1 file for source data. Figure 2—source data 1 Source data for Figure 2. https://cdn.elifesciences.org/articles/58641/elife-58641-fig2-data1-v2.xlsx Download elife-58641-fig2-data1-v2.xlsx Figure 3 with 1 supplement see all Download asset Open asset Reversible activation of BMP signaling using blue light-activated Opto-BMP. (A) Schematic of Opto-BMP strategy. Blue light-dimerizable VfLOV domains were fused to zebrafish BMP receptor kinase domains. Blue light exposure activates BMP signaling. (B) Embryos injected with mRNA encoding Opto-BMP at the one-cell stage and their uninjected siblings were reared in the dark or exposed to blue light for 10 h starting 70–80 min post-fertilization. Ventralization phenotypes V1-V4 (indicating excess BMP signaling) were scored at 1 day post-fertilization. Number of embryos: uninjected dark = 59, Opto-BMP dark = 53, uninjected light = 55, Opto-BMP light = 60. (C-E) Uninjected and Opto-BMP-injected embryos were exposed to blue light (2300 lux) for 30 min starting at high stage (3.5 hpf) or shield stage (6.75 hpf) and fixed during and after exposure. pSmad1/5/9 immunofluorescence was quantified and plotted in (C) as Opto-BMP minus uninjected signal with piecewise linear interpolation between timepoints; error bars represent standard error (see Materials and methods for statistical analysis). Blue background represents light exposure. Representative embryos from the high-stage (D) and shield-stage (E) experiments quantified in (C). pSmad1/5/9 signal is shown in magenta, DAPI in cyan. See the Figure 3—source data 1 file for source data. Figure 3—source data 1 Source data for Figure 3. https://cdn.elifesciences.org/articles/58641/elife-58641-fig3-data1-v2.xlsx Download elife-58641-fig3-data1-v2.xlsx Figure 4 Download asset Open asset Most BMP target genes are competent to respond to an early BMP signaling pulse. (A) Schematic of competence model: Late-activated genes should respond to a late (shield stage, solid line), but not early (high stage, dashed line) BMP signaling pulse. (B-O) High-confidence BMP target gene responses after an early (high stage,~3.5 hpf, dashed line) or late (shield stage,~6.75 hpf, solid line) BMP signaling pulse delivered by exposing uninjected and Opto-BMP-injected embryos to 30 min blue light (Figure 3C–E and Figure 3—figure supplement 1I,J). To assess induced transcription, NanoString transcript counts from uninjected embryos were subtracted from Opto-BMP transcript counts and are plotted here with piecewise linear interpolation between timepoints; error bars represent standard error (see Materials and methods for statistical analysis). See the Figure 4—source data 1 file for source data. Figure 4—source data 1 Source data for Figure 4. https://cdn.elifesciences.org/articles/58641/elife-58641-fig4-data1-v2.xlsx Download elife-58641-fig4-data1-v2.xlsx Figure 5 with 1 supplement see all Download asset Open asset Differential expression kinetics do not fully explain BMP target gene spatiotemporal diversity. (A) Different transcription kinetics may lead to differences in apparent activation times (arrowheads) based on assay detection thresholds (gray line). Assuming similar degradation kinetics, transcripts with faster induction rates should accumulate to higher levels in response to BMP. (B-E) Uninjected and Opto-BMP-injected embryos were exposed to blue light for 30 min at high (~3.5 hpf, B,C) or shield stage (~6.75 hpf, D,E), and target gene expression in response to the resulting BMP signaling pulses (Figure 3C–E and Figure 3—figure supplement 1I,J) was quantified using NanoString technology (Figure 4). Maximum average transcript counts were determined, and are plotted against activation time (B,D) (Figure 2) or spatial range (C,E). Error bars represent standard error, gray lines represent linear fits, ρs = Spearman correlation coefficient, ρp = Pearson correlation coefficient. crabp2b is not included due to lack of significant induction. (F-L) All three target gene response repeats were fitted with a model of induction and decay (Materials and methods). The average induction constant (σ) is plotted against activation time (F), spatial range (G), or maximum transcript count (J). The average decay constant (λ) is plotted against activation time (H), range (I), or maximum transcript count (K). Error bars represent standard error, ρs = Spearman correlation coefficient, ρp = Pearson correlation coefficient. crabp2b is not included due to lack of significant induction. pSmad1/5/9 immunofluorescence (Figure 3) was fitted with a polynomial (gray line, L) and used as signaling input. (M-Z) Individual fits of transcriptional responses (Figure 4); closed circles represent averages of three data points, open circles represent individual data points, and gray lines represent individual fits of each repeat. See the Figure 5—source data 1 source data file for source data. Figure 5—source data 1 Source data for Figure 5. https://cdn.elifesciences.org/articles/58641/elife-58641-fig5-data1-v2.xlsx Download elife-58641-fig5-data1-v2.xlsx Figure 6 with 1 supplement see all Download asset Open asset Differential sensitivity to BMP does not fully explain target gene expression diversity. (A) The activation threshold model predicts that broadly expressed genes will be activated by lower amplitude signaling. (B) pSmad1/5/9 immunofluorescence in uninjected and Opto-BMP-injected embryos exposed to 10 (triangle, dashed line) or 20 (diamond, solid line) min of 70 (light pink) or 3900 (magenta) lux blue light starting at shield stage. Immunofluorescence was quantified and plotted as Opto-BMP signal - uninjected with piecewise linear interpolation between timepoints; error bars represent standard error (see Materials and methods for statistical analysis). Embryos for the transcriptional response experiment were collected 30 (x), 40 (square), or 50 (circle) min after the start of light exposure. (C-F) Transcriptional responses in Opto-BMP embryos exposed to conditions shown in (B) were quantified using NanoString technology and are plotted against spatial range (C,E) or activation time (D,F). Embryos were collected 30 (x), 40 (square), or 50 (circle) min after the start of light exposure. Responses that are not statistically significant are anchored to the x-axis (N.S.; see Materials and methods for statistical analysis). See the Figure 6—source data 1 file for source data. Figure 6—source data 1 Source data for Figure 6. https://cdn.elifesciences.org/articles/58641/elife-58641-fig6-data1-v2.xlsx Download elife-58641-fig6-data1-v2.xlsx Figure 7 with 3 supplements see all Download asset Open asset FGF and Nodal contribute to the spatial diversity of BMP target genes. (A) pSmad1/5/9 immunofluorescence in untreated embryos at the indicated times (data also shown in Figure 1E). (B-E) Embryos were treated with 10 μM FGF inhibitor SU-5402 (B), 50 μM Nodal inhibitor SB-505124 (C), or both (D) starting at 2 hpf, or injected with 0.5 pg bmp2b mRNA at the one-cell stage (E). The BMP signaling gradient was quantified along the dorsal-ventral axis at shield stage using pSmad1/5/9 immunofluorescence; error bars represent standard error. Note that the embryos in panels B-E came from different experiments and were processed and imaged on different days, but untreated controls were always siblings of treated embryos and processed and imaged simultaneously. (F-J) BMP target gene expression along the dorsal-ventral axis at shield stage in untreated (F), SU-5402-treated (G), SB-505124-treated (H), SB-505124 + SU-5402-treated (I), and bmp-overexpressing (J) embryos quantified using fluorescence in situ hybridization (untreated data from Figure 1). (K) FGF and Nodal block expression of a subset of BMP target genes at the margin, and restrict BMP signaling in part by activating the BMP inhibitor Chordin. (L) Ventral views of margin-excluded BMP target gene expression at shield stage assessed by FISH in untreated embryos (top row), bmp-overexpressing embryos (0.5 pg bmp2b mRNA, middle row), and embryos treated with SU-5402 + SB-505124 (bottom row). Vertical white bars indicate regions where expression is excluded from the margin. (M) Expression levels at the margin quantified by calculating the average normalized intensity from 5–10% embryo length in untreated versus bmp-overexpressing embryos (left) or untreated versus SU-5402+SB-505124-treated embryos (right). Lines connect treated and untreated conditions to visualize shifts, error bars represent standard error. Lower numbers indicate less expression at the margin. (N) Spatial coefficient of variation for the 10 BMP target genes assessed here in untreated (black), SU-5402-treated (yellow), SB-505124-treated (red), SU-5402+SB-505124-treated (salmon), and bmp-overexpressing (magenta) embryos. Lower numbers indicate less spatial diversity. See the Figure 7—source data 1 file for source data. Figure 7—source data 1 Source data for Figure 7. https://cdn.elifesciences.org/articles/58641/elife-58641-fig7-data1-v2.xlsx Download elife-58641-fig7-data1-v2.xlsx Results BMP target genes have diverse spatiotemporal expression patterns We used RNA-sequencing to systematically identify genes activated by BMP during early zebrafish gastrulation, when BMP is engaged in dorsal-ventral patterning (shield stage,~6.75 h post-fertilization (hpf)) (Zinski et al., 2018). We identified 16 high-confidence target genes that are significantly upregulated in bmp-overexpressing embryos and downregulated in embryos overexpressing the BMP inhibitor chordin (Figure 1—figure supplement 1A–D and Supplementary file 1). 14 of these genes (apoc1l, bambia, bmp4, cdx4, eve1, foxi1, gata2a, id2a, klf2b, smad6a, smad7, sizzled, tfap2c, and ved) are known to be positively regulated by BMP in zebrafish (Kashiwada et al., 2015; Wang et al., 2015; Kotkamp et al., 2014; Wang et al., 2013; Das and Crump, 2012; de Pater et al., 2012; Kwon et al., 2010; Li and Cornell, 2007; Poulain et al., 2006; Chong et al., 2005; Davidson et al., 2003; Martyn and Schulte-Merker, 2003; Nissen et al., 2003; Solomon et al., 2003; Yabe et al., 2003; Pogoda and Meyer, 2002; Shimizu et al., 2002; Oates et al., 2001; Tsang et al., 2000; Chin et al., 1997; Nikaido et al., 1997; Hammerschmidt et al., 1996a; Hammerschmidt et al., 1996b; Mullins et al., 1996; Detrich et al., 1995; Joly et al., 1993; Joly et al., 1992), whereas crabp2b (Sharma et al., 2005) and znfl2b (Hogan et al., 2006) have not previously been implicated as BMP targets. Four of the 16 target genes encode repressors of BMP signaling (bambia, sizzled, smad6a, and smad7) and one encodes bmp4, consistent with roles for negative and positive feedbacks in TGF-β-mediated patterning (Zinski et al., 2018). According to the gradient threshold model, target genes are activated by distinct signaling levels, leading to different spatial domains of target gene expression in the presence of a signaling gradient (Figure 1A). To determine whether the BMP patterning system fits this paradigm, we first sought to characterize both BMP signaling distribution and spatial target gene expression. We assessed spatial BMP signaling from 2.75 to 7.25 hpf (256-cell stage – 60% epiboly) using immunofluorescent stainings to detect the BMP signal transducer pSmad1/5/9. We imaged embryos using selective plane illumination microscopy (SPIM) and quantified fluorescence along the dorsal-ventral axis (Figure 1—figure supplement 1E, Materials and methods). Similar to previous studies (Pomreinke et al., 2017; Zinski et al., 2017; Ramel and Hill, 2013; Tucker et al., 2008), we observed a ventrally-peaking BMP signaling gradient that increases in amplitude over time (Figure 1D,E). We then used fluorescence in situ hybridization and SPIM to quantify the spatial expression profiles of BMP target genes along the dorsal-ventral axis at shield stage (~6.75 hpf) and found that target genes have different expression profiles along this axis (Figure 1F–Y, Figure 1—figure supplement 1E, Materials and methods; some genes could not be quantified due to weak signal or inability to reliably identify the ventral side). The shape of the expression profiles can be well described by bell curves. We therefore used regression analysis with the Gaussian function Ae-x-μ2ς and defined the range of each target gene as r=μ+2ς/2 Using this definition, spatial gene expression broadness ranges from 40–100% dorsal-ventral embryo length (Figure 1F–Y). Strikingly, pronounced differences along the orthogonal animal-vegetal axis were also evident: Genes were either uniformly expressed along this axis on the ventral side (sizzled, ved, apoc1l, and bambia), restricted to the margin (cdx4 and eve1), or excluded from the margin (foxi1, klf2b, gata2a, and tfap2c) (Figure 1C,F–O’). Margin exclusion resulted in distinct dorsal-ventral profiles in which mRNA levels peak around 30% embryo length (Figure 1R,T,W,X), compared to non-excluded genes that peaked more ventrally (Figure 1P,Q,S,U,V,Y). Therefore, some of the spatial diversity in BMP target gene expression arises from differences along the animal-vegetal axis, orthogonal to the dorsal-ventral BMP signaling gradient. The gradient threshold paradigm (Figure 1A) implies that genes with broad ranges should be activated by lower signaling levels. Since signaling levels increase over time (Figure 1D,E; Pomreinke et al., 2017; Zinski et al., 2017; Ramel and Hill, 2013; Tucker et al., 2008), we sought to determine whether more broadly expressed targets were activated earlier. To assess temporal expression of BMP targets, we used NanoString molecular barcoding (Kulkarni, 2011) to measure transcript levels from 2.75 to 7.25 hpf (256-cell stage – 60% epiboly) (Figure 2A–N). The shape of the temporal expression profiles can be well approximated by the modified cumulative distribution function of the normal distribution 12A1+erf⁡x-ντ2+b We used this function for regression analysis of the temporal expression profiles and defined activation times as the average time point at which the curves reached about two mean average deviations (i.e., 1.5∙τ) from the inflection point ν. BMP target gene activation times defined in this way ranged from 3.4 to 6.3 hpf (Figure 2). The gradient threshold model predicts a monotonic decrease when comparing range and activation time. this is not observed for the (Figure is a monotonic when foxi1, eve1, and are excluded that in to the other the expression of and was quantified in the margin 1—figure supplement 1E, Materials and the that of BMP target genes may with the gradient threshold We therefore sought to investigate the between BMP signaling and target gene expression using an optogenetic strategy. Reversible optogenetic activation of BMP signaling in using Opto-BMP To assess how BMP target genes respond to BMP we a to optogenetically BMP signaling in We fused zebrafish BMP receptor kinase domains to an blue and et al., and the to the using a (Figure similar to previous et al., 2018; et al., 2018; et al., Blue light exposure should lead to of the domains and of the BMP kinase activating BMP signaling (Figure of mRNA encoding Opto-BMP zebrafish embryos at the one-cell stage resulted in ventralization in embryos, consistent with excess BMP whereas siblings were (Figure and Figure 3—figure supplement activation of BMP signaling was also using signaling activation (Figure 3—figure supplement To optogenetic we a light exposure by blue the of a standard and light intensity and dynamics with a (Figure 3—figure supplement Materials and methods). Using the we exposed uninjected and Opto-BMP-injected embryos to blue light for 30 min during high hpf) or shield hpf) fixed embryos during and after exposure, and quantified BMP signaling using pSmad1/5/9 immunofluorescence (Figure 3C–E and Figure 3—figure supplement 1I,J). both Opto-BMP embryos a increase in BMP signaling 10 min of light exposure, and signaling levels to normal after light These experiments that Opto-BMP activates BMP signaling in zebrafish embryos in response to Most BMP target genes are competent to respond to BMP at early stages BMP target genes are activated over a range of developmental from 3.4 to 6.3 hpf (Figure 2). differences in competence – a to respond to signaling – may the diversity in activation (Figure To we quantified BMP target gene expression in uninjected and Opto-BMP-injected embryos exposed to 30 min blue light during either high hpf) or shield stage hpf) (Figure 4 and Figure supplement In response to a BMP signaling pulse at high or shield stage (Figure 3C–E and Figure 3—figure supplement we observed significant pulses of BMP target gene expression for all genes and (Figure is not competent to respond to an early BMP signaling pulse and crabp2b not respond to either an early or late signaling all other high-confidence BMP target genes at high stage. Therefore, differences in competence to respond to BMP signaling at early stages do not explain the majority of diversity in activation kinetics in response to BMP do not fully explain spatiotemporal expression gene transcription kinetics can important roles in spatial expression domains. has been that Nodal target genes with faster transcript rates have spatial expression domains et al., 2015). To investigate how the transcription kinetics of BMP target genes may influence their spatiotemporal expression we assessed the dynamics of target gene responses (Figure to optogenetically generated BMP signaling pulses (Figure 3C–E and Figure 3—figure supplement 1I,J). We that the early activation and broad spatial range of some BMP targets be by more transcription in response to BMP. In this paradigm, early BMP signaling activates expression of all target genes at the but transcripts of more genes accumulate to levels at to to be (Figure spatial ranges could be by faster of transcripts that therefore be from the ventral side more To determine whether higher transcript rates with spatial ranges or earlier activation we first assessed maximum transcript counts in response to BMP signaling pulses at high or shield stage (Figure 4). Assuming similar transcript degradation kinetics, transcripts with faster rates should accumulate to higher levels in response to a BMP signaling pulse (Figure However, we observed a weak negative correlation (Figure or correlation (Figure between maximum transcript counts and activation and found similar results for range (Figure that differences in transcript rates in response to BMP do not fully account for differences in activation and spatial We then used a approach to assess transcript kinetics that does not the of similar transcript degradation rates (Figure We fitted the transcription data from the shield-stage BMP signaling pulse with a model the known pSmad1/5/9 (Figure Figure and Figure 3—figure supplement and transcript induction (σ) and decay (λ) (Figure Materials and methods). of the three repeats was fitted and average and were for each We found a weak negative correlation between and activation time (Figure and correlation between and range (Figure We also observed a weak negative correlation between and activation time (Figure and correlation between and spatial broadness (Figure These results are consistent with the maximum transcript count analysis (Figure and with an