107 Insights from roe deer oocyte transcriptome across embryonic diapause
S. M. Bernal-Ulloa A , V. A. van der Weijden A , J. T. Bick A , A. B. Rüegg A , B. Drews A and S. E. Ulbrich AETH Zurich, Animal Physiology, Institute of Agricultural Sciences, Zurich, Switzerland
Reproduction, Fertility and Development 31(1) 179-180 https://doi.org/10.1071/RDv31n1Ab107
Published online: 3 December 2018
Abstract
Embryonic developmental arrest, known as diapause, has been reported in more than 130 species. However, its mechanisms are still not completely understood. In the roe deer, the only known ungulate that exhibits this phenomenon, diapause lasts for approximately 5 months, starting after the rut period in mid-July to early August and ending with embryo elongation and implantation in December/January. Little is known regarding oocyte characteristics during this period. Here, we analysed the roe deer oocyte transcriptome as a model to understand diapause effects on oocyte features during embryonic developmental arrest and reactivation. During regular hunting, immature oocytes were obtained by ovary slicing from diapause and nondiapause stages, and classified according to morphological characteristics. Only oocytes with >2 layers of compact cumulus cells and cytoplasm from 30 hunted females were used for analyses. Immature oocytes were denuded and snap frozen. Additional oocytes were cultured in maturation medium for 20-24 h. Matured oocytes with a present polar body were snap frozen. Two pools of 10 immature and mature oocytes for both diapause and nondiapause stages were included (at least 4 donors/pool). Oocyte pools were processed using the Smart-seq 2 single-cell protocol (Illumina Inc., San Diego, CA, USA) for full-length cDNA and library preparation. We performed RNA-seq on an Illumina sequencer. The obtained Fastq files were clipped and analysed with a locally installed version of the Galaxy platform. Sequences were mapped against the roe deer transcriptome (unpublished data) and annotated against human and bovine transcripts. Differentially expressed genes (DEG; false discovery rate <1%) were identified using EdgeR (