A gene expression atlas of a bicoid-depleted drosophila embryo reveals early canalization of cell fate

Max V. Staller, Charless C. Fowlkes, Meghan D.J. Bragdon, Zeba Wunderlich, Javier Estrada, Angela H. Depace

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

In developing embryos, gene regulatory networks drive cells towards discrete terminal fates, a process called canalization. We studied the behavior of the anterior-posterior segmentation network in Drosophila melanogaster embryos by depleting a key maternal input, bicoid (bcd), and measuring gene expression patterns of the network at cellular resolution. This method results in a gene expression atlas containing the levels of mRNA or protein expression of 13 core patterning genes over six time points for every cell of the blastoderm embryo. This is the first cellular resolution dataset of a genetically perturbed Drosophila embryo that captures all cells in 3D. We describe the technical developments required to build this atlas and how the method can be employed and extended by others. We also analyze this novel dataset to characterize the degree and timing of cell fate canalization in the segmentation network. We find that in two layers of this gene regulatory network, following depletion of bcd, individual cells rapidly canalize towards normal cell fates. This result supports the hypothesis that the segmentation network directly canalizes cell fate, rather than an alternative hypothesis whereby cells are initially mis-specified and later eliminated by apoptosis. Our gene expression atlas provides a high resolution picture of a classic perturbation and will enable further computational modeling of canalization and gene regulation in this transcriptional network.

Original languageEnglish
Pages (from-to)587-596
Number of pages10
JournalDevelopment (Cambridge)
Volume142
Issue number3
DOIs
StatePublished - Feb 1 2015

Keywords

  • Bicoid
  • Canalization
  • Drosophila
  • Even-skipped
  • Gene expression atlas
  • Transcriptional network

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