Abstract
Next generation sequencing and mass spectrometry technologies have recently expanded the availability of whole transcriptomes and proteomes beyond classical model organisms in molecular biology, even in absence of an annotated genome. However, the fragmented nature of transcriptomic and proteomic data reduces the ability to interpret the data, notably in non-model organisms. Network-based approaches may help extracting important biological information from -omics datasets. The reproductive cycle of the freshwater crustacean Gammarus fossarum.provides an excellent case study to test the relevance of a network analysis in non-model organisms. Here, we illustrated how the use of a co-expression network analysis (based on Weighted Gene Co-expression Network Analysis algorithm, WGCNA) allowed identifying protein modules whose expression profiles described germ cell maturation and embryonic development in the freshwater crustacean Gammarus fossarum. Proteome datasets included testes, ovaries or embryos samples at different maturation or developmental stages, respectively. We identified an embryonic module correlated with mid-developmental stages corresponding to the organogenesis and it was characterized by enrichment in proteins involved in RNA editing and splicing. An ovarian module was enriched in vitellogenin-like proteins and clottable proteins, confirming the diversity of proteins belonging to the large lipid transfer family involved in oocytes maturations in this freshwater amphipod. Moreover, our results found evidence of a fine-tuned regulation between energy production by glycolysis and actin-myosin-dependent events in G. fossarum spermatogenesis. This study illustrates the importance of applying systems biology approaches to emergent animal models to improve the understanding of the molecular mechanisms regulating important physiological events with ecological relevance.
Highlights
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In order to have a systemic view of the molecular processes in the reproductive organs and in the embryonic development of the sentinel species G. fossarum, we analyzed proteomics data obtained from individually sampled testes and ovaries at different maturation status and from individually sampled embryos obtained at different developmental stages
We showed that Weighted Gene Co-expression Network Analysis (WGCNA) was well suited to extract biological information using shotgun proteomics data from a non-model organism
Summary
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. Generation sequencing and mass spectrometry technologies have recently expanded the availability of whole transcriptomes and proteomes beyond classical model organisms in molecular biology, even in absence of an annotated genome. The use of proteogenomics approaches, that couple species-specific RNA-sequencing followed by the acquisition of shotgun proteomic data by high-resolution mass spectrometry for a straightforward interpretation of peptide spectra, has opened the way to get insights into the molecular mechanisms involved in the physiology and the response to environmental stress in many species of ecological relevance[1,2]. The fragmented nature of proteomic and transcriptomic data without a reference genome usually prevents extensive interpretation of the data This is true in the context of the molecular physiology of non-model organisms whose genomes are evolutionarily distant from well-annotated genomes, such as those of the fly D. melanogaster or the human genome. Network-based approaches provide an excellent methodological www.nature.com/scientificreports/
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