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. 2025 Jul 1;152(13):dev204460.
doi: 10.1242/dev.204460. Epub 2025 Jul 3.

Bulk-level maps of pioneer factor binding dynamics during the Drosophila maternal-to-zygotic transition

Affiliations

Bulk-level maps of pioneer factor binding dynamics during the Drosophila maternal-to-zygotic transition

Sadia Siddika Dima et al. Development. .

Abstract

Gene regulation by transcription factors (TFs) binding cognate sequences is of paramount importance. For example, the TFs Zelda (Zld) and GAGA factor (GAF) are widely acknowledged for pioneering gene activation during zygotic genome activation (ZGA) in Drosophila. However, quantitative dose/response relationships between bulk TF concentration and DNA binding, an event tied to transcriptional activity, remain elusive. Here, we map these relationships during ZGA: a crucial step in metazoan development. To map the dose/response relationship between nuclear concentration and DNA binding, we performed raster image correlation spectroscopy, a method that can measure biophysical parameters of fluorescent molecules. We found that, although Zld concentration increases during nuclear cycles 10 to 14, its binding in the transcriptionally active regions decreases, consistent with its function as an activator for early genes. In contrast, GAF-DNA binding is nearly linear with its concentration, which sharply increases during the major wave, implicating its involvement in the major wave. This study provides key insights into the properties of the two factors and puts forward a quantitative approach that can be used for other TFs to study transcriptional regulation.

Keywords: DNA binding; GAGA factor; Pioneer factors; Raster image correlation spectroscopy; Zelda; Zygotic genome activation.

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Conflict of interest statement

Competing interests The authors declare no competing or financial interests.

Figures

Fig. 1.
Fig. 1.
Raster Image Correlation Spectroscopy (RICS). (A) Laser scanning confocal microscopes build images by raster scan, with a fast scanning direction (x direction, solid arrows) and a slow scanning direction (y direction) due to line retracing (dashed arrows). Image shows a mid-nc14 embryo expressing sfGFP-Zld. (B) Two-dimensional autocorrelation function (ACF) from the embryo depicted in A. Cuts along the fast (blue circles) and slow (orange circles) directions are depicted. (C) Cut of ACF along the fast direction. Solid curve: fit of Gaussian-shaped PSF, used to estimate the ACF amplitude, A. (D) Plot of the slow direction data (circles) and the fit to the slow direction (solid curve), composed of a linear combination between two ACFs (gray dotted curves): an immobile ACF formula image and a diffusible ACF formula image. The linear combination weight is φ, the immobile fraction. (E) Plots of cuts of the cross correlation function (CCF; blue circles) and of the ACF in the red channel (orange circles). The ratio of the amplitudes (Acc/Ared) is proportional to ψ, the fraction bound in active regions of the DNA. (F) Illustration of the different pools of TF: freely diffusible (light blue), bound to active regions (dark blue) and bound to inactive regions (yellow). His2Av (purple) is associated with the active regions of DNA.
Fig. 2.
Fig. 2.
Quantification of the biophysical parameters and dynamics of Zld. (A) Representative images of a sfGFP-Zld embryo used for Raster Image Correlation Spectroscopy (RICS) analysis from nc 10 to nc 14, as indicated. (B-D) Dynamics of different pools of sfGFP-Zld from nc 10 until gastrulation, including total nuclear concentration (B), immobile fraction (C) and active fraction (D). Data are mean±s.e.m. (n=20 embryos). (E) Dose/response map between total nuclear concentration of Zld and the immobile (both active and inactive) concentration of Zld. The solid line represents the model fit for the active population and the dashed line represents the same for the inactive population. (F) Change in Zld sites accessible for binding over time. See also Fig. S1 and Movie 1.
Fig. 3.
Fig. 3.
Quantification of the biophysical parameters and dynamics of GAF. (A) Representative images of a GAF-sfGFP(C) embryo used for Raster Image Correlation Spectroscopy (RICS) analysis from nc 10 to nc 14, as indicated. (B-D) Dynamics of the parameters from nc 10 until gastrulation, including total nuclear concentration (B), the immobile fraction (C) and the active fraction (D). Data are mean±s.e.m. (n=19 embryos). (E) Dose/response map between total nuclear concentration of GAF and the immobile (both active and inactive) concentration of GAF. The solid line represents the model fit for the active population and the dashed line represents the same for the inactive population. See also Fig. S3 and Movie 2.
Fig. 4.
Fig. 4.
Role of pioneer factors Zld and GAF during Drosophila ZGA. During the minor wave of ZGA, a high concentration of Zld (yellow circles) bound to its sites (yellow lines) in the active regions allows it to act as the main activator of early genes. This active bound concentration reduces during the major wave, when the concentration of GAF (magenta circles) bound to the sites (magenta lines) in the active regions increases, after saturating the sites in the inactive regions. This allows GAF to act as the main activator of the genes that begin to be expressed during the major wave.

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References

    1. Al Asafen, H., Clark, N. M., Goyal, E., Jacobsen, T., Dima, S. S., Chen, H.-Y., Sozzani, R. and Reeves, G. T. (2024). Dorsal/NF-κB exhibits a dorsal-to-ventral mobility gradient in the Drosophila embryo. eLife 13, rp100462. 10.7554/eLife.100462.1 - DOI
    1. Antonin, W. and Neumann, H. (2016). Chromosome condensation and decondensation during mitosis. Curr. Opin. Cell Biol. 40, 15-22. 10.1016/j.ceb.2016.01.013 - DOI - PubMed
    1. Ay, A. and Arnosti, D. N. (2011). Mathematical modeling of gene expression: a guide for the perplexed biologist. Crit. Rev. Biochem. Mol. Biol. 46, 137-151. 10.3109/10409238.2011.556597 - DOI - PMC - PubMed
    1. Bacia, K. and Schwille, P. (2007). Practical guidelines for dual-color fluorescence cross-correlation spectroscopy. Nat. Protoc. 2, 2842-2856. 10.1038/nprot.2007.410 - DOI - PubMed
    1. Bellec, M., Dufourt, J., Hunt, G., Lenden-Hasse, H., Trullo, A., Zine El Aabidine, A., Lamarque, M., Gaskill, M. M., Faure-Gautron, H., Mannervik, M.et al. (2022). The control of transcriptional memory by stable mitotic bookmarking. Nat. Commun. 13, 1176. 10.1038/s41467-022-28855-y - DOI - PMC - PubMed

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