A pilot study on transcriptome data analysis of folliculogenesis in pigs
G. Tosser-Klopp,
K.-A. Lê Cao,
A. Bonnet,
N. Gobert,
F. Hatey,
C. Robert-Granié,
S. Déjean,
J. Antic,
L. Baschet,
M. SanCristobal
Affiliations
G. Tosser-Klopp
Laboratoire de Génétique Cellulaire, Institut National de la Recherche Agronomique, UMR444, BP 52627, 31326 Castanet Tolosan Cedex, France
K.-A. Lê Cao
Station d’Amélioration Génétique des Animaux, Institut National de la Recherche Agronomique (UR631), BP 52627, 31326 Castanet Tolosan Cedex, France; Institut de Mathématiques, Université de Toulouse et Centre National de la Recherche Scientifique (UMR5219), 31062 Toulouse Cedex 9, France
A. Bonnet
Laboratoire de Génétique Cellulaire, Institut National de la Recherche Agronomique, UMR444, BP 52627, 31326 Castanet Tolosan Cedex, France
N. Gobert
Laboratoire de Génétique Cellulaire, Institut National de la Recherche Agronomique, UMR444, BP 52627, 31326 Castanet Tolosan Cedex, France
F. Hatey
Laboratoire de Génétique Cellulaire, Institut National de la Recherche Agronomique, UMR444, BP 52627, 31326 Castanet Tolosan Cedex, France
C. Robert-Granié
Station d’Amélioration Génétique des Animaux, Institut National de la Recherche Agronomique (UR631), BP 52627, 31326 Castanet Tolosan Cedex, France
S. Déjean
Institut de Mathématiques, Université de Toulouse et Centre National de la Recherche Scientifique (UMR5219), 31062 Toulouse Cedex 9, France
J. Antic
Département de Génie Mathématique et Modélisation, INSA, 135, Avenue de Rangueil, 31077 Toulouse Cedex 4, France
L. Baschet
Département de Génie Mathématique et Modélisation, INSA, 135, Avenue de Rangueil, 31077 Toulouse Cedex 4, France
M. SanCristobal
Laboratoire de Génétique Cellulaire, Institut National de la Recherche Agronomique, UMR444, BP 52627, 31326 Castanet Tolosan Cedex, France
Three different stages of pig antral follicles have been studied in a granulosa-cell transcriptome analysis on nylon microarrays (1152 clones). The data have been generated from seven RNA follicle pools and several technical replicates were made. The objective of this paper was to state the feasibility of a transcriptomic protocol for the study of folliculogenesis in the pig. A statistical analysis was chosen, relying on the linear mixed model (LMM) paradigm. Low variability within technical replicates was hence checked with a LMM. Relevant genes that might be involved in the studied process were then selected. For the most significant genes, statistical methods such as principal component analysis and unsupervised hierarchical clustering were applied to assess their relevance, and a random forest analysis proved their predictive value. The selection of genes was consistent with previous studies and also allowed the identification of new genes whose role in pig folliculogenesis will be further investigated.
