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Preprints

Rabbit Development as a Model for Single Cell Comparative Genomics

Ton MN, Keitley D, Theeuwes B, Guibentif C, Ahnfelt-Rønne J, Andreassen TK, Calero-Nieto FJ, Imaz-Rosshandler I, Pijuan-Sala B, Nichols J, Benito-Gutiérrez È, Marioni JC, Göttgens B.
Preprint from
bioRxiv
6 October 2022
PPR
PPR555015
Abstract

ABSTRACT

Biomedical research relies heavily on the use of model organisms to gain insight into human health and development. Traditionally, the mouse has been the favored vertebrate model, due to its experimental and genetic tractability. Non-rodent embryological studies however highlight that many aspects of early mouse development, including the egg-cylinder topology of the embryo and its method of implantation, diverge from other mammals, thus complicating inferences about human development. In this study, we constructed a morphological and molecular atlas of rabbit development, which like the human embryo, develops as a flat-bilaminar disc. We report transcriptional and chromatin accessibility profiles of almost 180,000 single cells and high-resolution histology sections from embryos spanning gastrulation, implantation, amniogenesis, and early organogenesis. Using a novel computational pipeline, we compare the transcriptional landscape of rabbit and mouse at the scale of the entire organism, revealing that extra-embryonic tissues, as well as gut and PGC cell types, are highly divergent between species. Focusing on these extra-embryonic tissues, which are highly accessible in the rabbit, we characterize the gene regulatory programs underlying trophoblast differentiation and identify novel signaling interactions involving the yolk sac mesothelium during hematopoiesis. Finally, we demonstrate how the combination of both rabbit and mouse atlases can be leveraged to extract new biological insights from sparse macaque and human data. The datasets and analysis pipelines reported here set a framework for a broader cross-species approach to decipher early mammalian development, and are readily adaptable to deploy single cell comparative genomics more broadly across biomedical research.