196 Oral - Techniques and Technology Session
Saturday April 09, 5:00 PM - 5:15 PM

Authors:
Xingfan Huang ^2,3; Ronnie Blecher-Gonen ¹; Diego Calderon ²; Riza Daza ²; Stefano Secchia ⁷; Beth Martin ²; Baekgyu Kim ⁷; Alessandro Dulja ⁷; Cole Trapnell ²; Eileen Furlong ⁷; Jay Shendure ^2,4,5,6

Affiliations:
1) The Crown Genomics institute of the Nancy and Stephen Grand Israel National Center for Personalized Medicine, Weizmann Institute of Science, Israel; 2) Department of Genome Sciences, University of Washington, Seattle, WA ; 3) Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA ; 4) Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA; 5) Howard Hughes Medical Institute, Seattle, WA; 6) Allen Discovery Center for Cell Lineage Tracing, Seattle, WA; 7) European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany

Keywords:
p. single cell sequencing; m. computational models

Single cell technologies are a powerful new means to study metazoan development, enabling comprehensive surveys of cellular diversity at profiled timepoints, and shedding light on the dynamics of regulatory element activity and gene expression changes during the in vivo emergence of each cell type. However, nearly all such atlases of embryogenesis remain limited by sampling density, i.e. the number of discrete time points at which individual embryos are harvested. Given the rapidity with which molecular and cellular programs unfold, this limits the resolution at which regulatory transitions can be characterized.

To construct a continuous representation of embryogenesis in vivo, we would ideally sample embryos continuously. Although not possible with most model organisms, it is potentially possible in Drosophila melanogaster, where collections of timed and yet somewhat asynchronous embryos are easy to obtain. Drosophila could therefore serve as a test case to develop a framework for the inference of continuous regulatory and cellular trajectories as embryogenesis progresses. Of course, as Drosophila is a preeminent model organism that has yielded many advances in the biological and biomedical sciences, obtaining a single cell atlas of Drosophila embryogenesis is also an important goal in itself.

In this study, we report a continuous, single cell atlas of chromatin accessibility and gene expression that spans Drosophila embryogenesis. We profiled chromatin accessibility in almost one million, and gene expression in half a million, nuclei from eleven tightly staged, overlapping windows of 0 through 20 hours of embryogenesis. Leveraging the asynchronicity of embryos within each collection window, we developed a statistical model to estimate the age of each nucleus more precisely, resulting in continuous views of molecular and cellular transitions throughout embryonic development. From these data, we identify cell types, infer their developmental relationships, and link cell type-specific changes in transcription factor expression to changes in the accessibility of their cognate motifs. Looking forward, this strategy may facilitate future investigations of in vivo gene regulation throughout Drosophila embryogenesis at arbitrarily high temporal resolution.