Development across evolutionary time at a single cell resolution in the Caenorhabditis nematodes
Authors: Christopher Large 1; Rupa Khanal 2; Qin Zhu 3; Priya Sivaramakrishnan 1; Felicia Peng 1; Erik Nordgren 2; Jean Rosario 2; Junhyong Kim 2; John Murray 1
Affiliations: 1) Department of Genetics, University of Pennsylvania, Philadelphia, PA; 2) Department of Biology, University of Pennsylvania, Philadelphia, PA; 3) Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA
Keywords: Comparative genomics & genome evolution
Complex gene regulatory networks specify the development of all multicellular organisms and determine the morphological complexity of life. What determines the rate of change and the evolutionary constraint of cellular gene expression patterns across development remains a fundamental question of biology. Previous measurements of morphology and gene expression across developmental stages in whole organisms have led to the establishment of the hourglass model which posits that the developmental plan is under the highest constraint during the midpoint of development. However, the relevance of these observations for individual cell and tissue types is unclear, harming the predictive power of the model and leaving open questions as to the model's biological underpinnings. Historically, the ability to systematically profile homologous cells across different organisms for their function and transcriptional profile has been limited by technology, however single cell sequencing has facilitated the ability to capture and molecularly label individual cells through microfluidics. Each cell’s identity, developmental timing, and physical location in the organism can then be determined by comparing the cell’s transcriptional profile to reference developmental markers with known expression patterns. Using single cell sequencing, we are currently measuring the spatiotemporal divergence of gene expression across evolutionary time within the Caenorhabditis nematodes by comparing the transcriptomes of homologous cells and tissues between species across embryonic development. Altogether, we will elucidate the constraints on gene regulatory network evolution by building and comparing molecular atlases of development for >10 Caenorhabditis species. We plan to use the multispecies single cell-atlases to determine the rate of divergence of cell and gene expression patterns across the Caenorhabditis phylogeny, providing insight into how new cell types are born, the fate of recent gene duplications, and how the life histories of the Caenorhabditis species influence their evolution.