A pilot study on transcriptome data analysis of folliculogenesis in pigs

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.

Keywords

• microarray
• pig
• folliculogenesis
• statistical data analysis