English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The quality of follicular oocytes depends on interactions with surrounding granulosa cells. Development of molecular techniques and methods enables better understanding of processes underlying mammalian reproduction on cellular level. The success in reproductive biology and medicine in different species depends on reliable assessment of oocyte and embryo viability which presently mainly bases on embryo morphology. Although successful pregnancies have been achieved using this approach, its precision still should be improved and completed with other, more objective, and accurate assessment strategies. Global profiling of gene expression in follicular cumulus cells using microarrays is continuously leading to the establishment of new biomarkers which can be used to select oocytes with highest developmental potential. Even more potential applications and greater precision could be achieved using next generation sequencing (NGS) of granulosa and cumulus cell RNA (RNA-seq). However, due to the high cost, this method is not used as frequently as microarrays at the moment. In any case, high-throughput technologies offer the possibilities and advantages in ovarian somatic cell analysis on scale that has not been noted so far. The aim of this work is to present current directions and examples of global molecular profiling of granulosa cells and underline its impact on reproductive biology and medicine.

High-Throughput Analysis of Ovarian Granulosa Cell Transcriptome