Opportunities and challenges in applying genomics to the study of oogenesis and follicullogenesis in farm animals
2008
Bonnet , Agnes (INRA , Auzeville (France). UMR 0444 Laboratoire de Génétique Cellulaire) | Dalbiès-Tran , Rozenn (INRA , Nouzilly (France). UMR 0085 Physiologie de la Reproduction et des Comportements) | Sirard , M.A. (Université Laval(Canada). Centre de Recherche en Biologie de la Reproduction)
Ovarian oogenesis and folliculogenesis are complex and coordinated biological processes which require a series of events that induce morphological and functional changes within the follicle, leading to cell differentiation and oocyte development. In this context, the challenge of the researchers is to describe the dynamics of gene expression in the different compartments and their interactions during the follicular programme. In recent years, high-throughput arrays have become a powerful tool with which to compare the whole population of transcripts in a single experiment. Here, we review the challenges of applying genomics to this model in farm animal species. The first limitation lies in limited the availability of biological material, which makes the study of the follicle compartments (oocyte, granulosa cells and thecal cells) or early embryo much more difficult. The concept of observing all transcripts at once is very attractive but despite progress in sequencing, the genome annotation remains very incomplete in non-model species. Particularly, oogenesis and early embryo development relate to the high proportion of unknown expressed sequence tags. Then, it is important to consider post-transcriptional and translational regulation to understand the role of these genes. Ultimately, these new inferred insights will still have to be validated by functional approaches. In addition to in vitro or ex vivo functional approaches, both 'natural mutant' ewe models and RNA interference represent, at the moment, the best hope for functional genomics. Advances in our understanding of reproductive physiology should be facilitated by gene expression data exchange and translation into a better understanding of the underlying biological phenomena.
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