The continuum of Drosophila embryonic development at single-cell resolution.
Diego CalderonRonnie Blecher-GonenXingfan HuangStefano SecchiaJames KentroRiza M DazaBeth K MartinAlessandro DuljaChristoph SchaubCole TrapnellErica LarschanKate M Oâ Connor-GilesEileen E M FurlongJay ShendurePublished in: Science (New York, N.Y.) (2022)
Drosophila melanogaster is a powerful, long-standing model for metazoan development and gene regulation. We profiled chromatin accessibility in almost 1 million and gene expression in half a million nuclei from overlapping windows spanning the entirety of embryogenesis. Leveraging developmental asynchronicity within embryo collections, we applied deep neural networks to infer the age of each nucleus, resulting in continuous, multimodal views of molecular and cellular transitions in absolute time. We identify cell lineages; infer their developmental relationships; and link dynamic changes in enhancer usage, transcription factor (TF) expression, and the accessibility of TFs' cognate motifs. With these data, the dynamics of enhancer usage and gene expression can be explored within and across lineages at the scale of minutes, including for precise transitions like zygotic genome activation.
Keyphrases
- gene expression
- transcription factor
- single cell
- drosophila melanogaster
- neural network
- binding protein
- dna methylation
- rna seq
- genome wide identification
- poor prognosis
- dna binding
- single molecule
- high throughput
- cell therapy
- electronic health record
- big data
- long non coding rna
- dna damage
- bone marrow
- pregnant women
- mesenchymal stem cells
- chronic pain
- deep learning