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A pilot study on transcriptome data analysis of folliculogenesis in pigs

Published online by Cambridge University Press:  01 March 2009

G. Tosser-Klopp*
Affiliation:
Laboratoire de Génétique Cellulaire, Institut National de la Recherche Agronomique, UMR444, BP 52627, 31326 Castanet Tolosan Cedex, France
K.-A. Lê Cao
Affiliation:
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
Affiliation:
Laboratoire de Génétique Cellulaire, Institut National de la Recherche Agronomique, UMR444, BP 52627, 31326 Castanet Tolosan Cedex, France
N. Gobert
Affiliation:
Laboratoire de Génétique Cellulaire, Institut National de la Recherche Agronomique, UMR444, BP 52627, 31326 Castanet Tolosan Cedex, France
F. Hatey
Affiliation:
Laboratoire de Génétique Cellulaire, Institut National de la Recherche Agronomique, UMR444, BP 52627, 31326 Castanet Tolosan Cedex, France
C. Robert-Granié
Affiliation:
Station d’Amélioration Génétique des Animaux, Institut National de la Recherche Agronomique (UR631), BP 52627, 31326 Castanet Tolosan Cedex, France
S. Déjean
Affiliation:
Institut de Mathématiques, Université de Toulouse et Centre National de la Recherche Scientifique (UMR5219), 31062 Toulouse Cedex 9, France
J. Antic
Affiliation:
Département de Génie Mathématique et Modélisation, INSA, 135, Avenue de Rangueil, 31077 Toulouse Cedex 4, France
L. Baschet
Affiliation:
Département de Génie Mathématique et Modélisation, INSA, 135, Avenue de Rangueil, 31077 Toulouse Cedex 4, France
M. SanCristobal
Affiliation:
Laboratoire de Génétique Cellulaire, Institut National de la Recherche Agronomique, UMR444, BP 52627, 31326 Castanet Tolosan Cedex, France
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Abstract

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.

Type
Full Paper
Copyright
Copyright © The Animal Consortium 2008

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Footnotes

a

These authors have contributed equally to this work.

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