Statistical analysis of the individual variability of 1D protein profiles as a tool in ecology: an application to parasitoid venom

Hugo Mathe-Hubert (1) , Jean Luc Gatti (1) , Dominique Colinet (1) , M. Poirié (2) , T. Malausa (3)

1 ISA - Institut Sophia Agrobiotech
2 LEGS - Laboratoire Evolution, Génomes et Spéciation
3 EDB - Evolution et Diversité Biologique

Understanding the forces that shape eco-evolutionary patterns often requires linking phenotypes to genotypes, allowing characterization of these patterns at the molecular level. DNA-based markers are less informative in this aim compared to markers associated with gene expression and, more specifically, with protein quantities. The characterization of eco-evolutionary patterns also usually requires the analysis of large sample sizes to accurately estimate interindividual variability. However, the methods used to characterize and compare protein samples are generally expensive and time-consuming, which constrains the size of the produced data sets to few individuals. We present here a method that estimates the interindividual variability of protein quantities based on a global, semi-automatic analysis of 1D electrophoretic profiles, opening the way to rapid analysis and comparison of hundreds of individuals. The main original features of the method are the in silico normalization of sample protein quantities using pictures of electrophoresis gels at different staining levels, as well as a new method of analysis of electrophoretic profiles based on a median profile. We demonstrate that this method can accurately discriminate between species and between geographically distant or close populations, based on interindividual variation in venom protein profiles from three endoparasitoid wasps of two different genera (Psyttalia concolor, Psyttalia lounsburyi and Leptopili-na boulardi). Finally, we discuss the experimental designs that would benefit from the use of this method.

Mots clés: individual 1D SDS-PAGE; non-neutral markers; parasitoid venom; population proteomics; Quantitative variation; proteins

Domaines: Imagerie médicale; Traitement des images [eess.IV]; Biochimie [q-bio.BM]; Imagerie; Applications [stat.AP]; Ecosystèmes; Biodiversité et Ecologie

Hugo Mathe-Hubert, Jean Luc Gatti, Dominique Colinet, M. Poirié, T. Malausa. Statistical analysis of the individual variability of 1D protein profiles as a tool in ecology: an application to parasitoid venom. Molecular Ecology Resources, 2015, 15 (5), pp.1120-1132. ⟨10.1111/1755-0998.12389⟩. ⟨hal-02168210⟩