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Published February 19, 2016 | Accepted Version + Supplemental Material
Journal Article Open

Quantitative Single-Embryo Profile of Drosophila Genome Activation and the Dorsal-Ventral Patterning Network

Abstract

During embryonic development of Drosophila melanogaster, the Maternal to Zygotic Transition (MZT) marks a significant and rapid turning point when zygotic transcription begins and control of development is transferred from maternally deposited transcripts. Characterizing the sequential activation of the genome during the MZT requires precise timing and a sensitive assay to measure changes in expression. We utilized the NanoString nCounter instrument, which directly counts mRNA transcripts without reverse transcription or amplification, to study over 70 genes expressed along the dorsal-ventral (DV) axis of early Drosophila embryos, dividing the MZT into 10 time points. Transcripts were quantified for every gene studied at all time points, providing the first data set of absolute numbers of transcripts during Drosophila development. We found that gene expression changes quickly during the MZT, with early Nuclear Cycle (NC) 14 the most dynamic time for the embryo. twist is one of the most abundant genes in the entire embryo and we use mutants to quantitatively demonstrate how it cooperates with Dorsal to activate transcription and is responsible for some of the rapid changes in transcription observed during early NC14. We also uncovered elements within the gene regulatory network that maintain precise transcript levels for sets of genes that are spatiotemporally co-transcribed within the presumptive mesoderm or dorsal ectoderm. Using this new data, we show that a fine-scale, quantitative analysis of temporal gene expression can provide new insights into developmental biology by uncovering trends in gene networks including coregulation of target genes and specific temporal input by transcription factors.

Additional Information

© 2016 Genetics Society of America. Manuscript received January 4, 2016; accepted for publication February 4, 2016; published Early Online February 18, 2016. We thank and dedicate this paper to Eric Davidson (1937-2105), a co-developer of NanoString technology, for helpful discussions and guidance, and who generously provided use of his NanoString instrument for this study. We also thank past and present Davidson Laboratory members Julius Barsi, Roberto Feuda, and Stefan Materna for technical assistance, advice using the NanoString instrument and in data analysis, and comments on the manuscript. This work was funded by grant R01GM077668 from the National Institute of Health to A.S.

Attached Files

Accepted Version - genetics.116.186783.full.pdf

Supplemental Material - FigureS1.pdf

Supplemental Material - FigureS2.pdf

Supplemental Material - TableS1.pdf

Supplemental Material - TableS2.pdf

Supplemental Material - TableS3.pdf

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Created:
August 22, 2023
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October 17, 2023