Transcriptomic Analysis of Bovine Cumulus Cells Investment of Oocytes at Different Stage of Differentiation Based on the Degree of Their Chromatin Configuration: Preliminary Study

The identification of biomarkers that can predict oocyte viability and developmental potential has important implications in treating human infertility as well as managing breeding schemes of domestic mammals. During ovarian follicle development, interactions between somatic and germ cells are critical for normal follicular and oocyte development as well as for the acquisition of oocyte competence. Moreover, companion granulosa cells serve a critical role in the regulation of global transcriptional silencing and in the modulation of chromatin configuration changes that occur before meiotic resumption. Importantly, chromatin configurations within the oocyte germinal vesicle (GV) are indicative of oocytes metabolic state as well as in vitro developmental potential. However, the mechanisms acting in the somatic compartment that regulate oocyte differentiation and competence are far from being fully understood. Starting from these observations, the aim of this study was to assess gene expression profile by microarray platform in cumulus cells (CC) isolated from ovarian follicles, which may be linked to the oocyte developmental competence. To this aim we have determined the expression profile of CC investment of oocytes at different stage of differentiation, and selected according to their chromatin configuration by DNA staining. Oocytes were classified as GV0, GV1, GV2 and GV3 according to their chromatin pattern. CC belonging to each group were collected and processed for further analysis. Four pools of CC from 10 oocytes per group were used. RNA was extracted, amplified and hybridized on a bovine embryo-specific 44K Agilent slide (EmbryoGene). The GV1, GV2 and GV3 classes were each hybridized against the GV0, which represents a stage of early oocyte differentiation with poor development competence. Data were normalized with Loess and Fold changes (FC) of differentially expressed genes were determined with Limma procedure. Finally, the regulation pattern genes and function predicted was studied with Ingenuity Pathway Analysis software. Transcriptome analysis (FC >1.5; p