P0168
Integrated Muscle Analysis of Transcriptome and Proteome of Piglet Maturity

Date: Monday, January 12, 2015
Room:
Valentin Voillet , INRA UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet, France
Magali San Cristobal , INRA-GenPhySE, Castanet, France
Marie-Christine Père , INRA UMR1348 Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Élevage, Saint-Gilles, France
Laurianne Canario , INRA UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet, France
Yvon Billon , INRA, UE1372 GenESI, Saint-Pierre-d'Amilly, France
Louis Lefaucheur , INRA UMR1348 Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Élevage, Saint-Gilles, France
Laurence Liaubet , INRA UMR1388 Génétique, Physiologie et Systèmes d’Elevage, Castanet, France
Whilst transcriptomic analysis has provided incredible insight into cell operation, an integrated multi-omics approach is crucial to gain further knowledge into complex biological systems. In particular, the integration of the transcriptome and proteome is a current challenge in omics and biomarkers research.

Piglet maturation, which occurs at the end of gestation, leads to the state of full development and is an important determinant of early survival. The objective of our project is an integrated multi-omics approach (transcriptomics, proteomics and phenotypes) with focus on muscle metabolism, because of its key role in adaptation to extra-uterine life.

Progeny from two breeds, Large White (LW) and Meishan (MS), contrasting for maturity at birth were produced in a crossbreeding design based on the use of mixed semen. The LW is a selected breed with an increased rate of mortality at birth, whereas the MS breed produces robust piglets. Muscle maturity was analyzed on the progeny from these two breeds and the reciprocal F1 at the end of gestation (gestational days 90 and 110).

First, some key biological processes (gluconeogenesis / glycolysis) and crucial genes explaining the biological muscle maturity difference between the two extreme purebred piglets were highlighted.

Then, some statistical methods including sparse Partial Least Square and network mining (Gaussian Graphical Model) were performed between the two levels of expression. Patterns of transcriptome and proteome were investigated by construction of individual networks. Bipartite links between proteome and transcriptome, via sPLS, will allow to determine possible biomarkers of maturity.

Funds: PORCINET ANR-09-GENM-005, Région Midi-Pyrénées