Proceedings of the National Academy of SciencesDevelopmental BiologyPeer-reviewed journal article
Distinct gene expression dynamics in developing and regenerating limbs
Chiara SinigagliaiD, Alba AlmazániD, Marie LebeliD, Marie SémoniD, Benjamin GilletiD, Sandrine HughesiD, Eric EdsingeriD, Michalis AverofiD, Mathilde ParisiD
Abstract
Regenerating animals have the ability to reproduce organs that were originally generated in the embryo and subsequently lost due to injury. Understanding whether the process of regeneration mirrors development is an open question in most regenerative species. Here we take a transcriptomics approach to examine to what extent leg regeneration shows the same temporal patterns of gene expression as leg development in the embryo, in the crustacean Parhyale hawaiensis. We find that leg development in the embryo shows stereotypic temporal patterns of gene expression. In contrast, global patterns of gene expression during leg regeneration show a high degree of variation, related to the physiology of individual animals. A major driver of this variation is the molting cycle. After dissecting the transcriptional signals of individual physiology from regeneration, we obtain temporal signals that mark distinct phases of leg regeneration. Comparing the transcriptional dynamics of development and regeneration we find that, although both processes use largely the same genes, the temporal patterns in which these gene sets are deployed are different and cannot be systematically aligned. HIGHLIGHTSO_LISingle-limb data on transcriptional dynamics of leg development and regeneration C_LIO_LIDeveloping embryonic legs show stereotypic transcriptional profiles C_LIO_LIRegenerating leg transcriptomes show a high degree on individual variation C_LIO_LIRegenerating leg transcriptomes are influenced by adult physiology, especially molting C_LIO_LIRegenerating leg transcriptomes reveal distinct phases of leg regeneration C_LIO_LILeg development and regeneration use overlapping sets of genes in different temporal patterns C_LI
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: trajectory inference
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 57
- FWCI
- 4.82
- Field percentile
- top 3%
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