scRNA-seq of ovarian follicle granulosa cells from different fertility goats reveals distinct expression patterns

Reprod Domest Anim. 2021 May;56(5):801-811. doi: 10.1111/rda.13920. Epub 2021 Mar 19.

Abstract

The new technology of high-throughput single-cell RNA sequencing (10 × scRNA-seq) was developed recently with many advantages. However, it was not commonly used in farm animal research. There are few reports for the gene expression of goat ovarian follicle granulosa cells (GCs) during different developmental stages. In the current investigation, the gene expression of follicle GCs at different stages from two populations of Ji'ning grey goats: high litter size (HL; ≥3/L; 2 L) and low litter size (LL; ≤2 /L; 2 L) were analysed by scRNA-seq. Many GC marker genes were identified, and the pseudo-time showed that GCs developed during the time course which reflected the follicular development and differentiation trajectory. Moreover, the gene expression difference between the two populations HL versus LL was very clear at different developmental stages. Many marker genes differentially expressed at different developmental stages. ASIP and ASPN were found to be highly expressed in the early stage of GCs, INHA, INHBA, MFGE8 and HSD17B1 were identified to be highly expressed in the growing stage of GCs, while IGFBP2, IGFBP5 and CYP11A1 were found to be highly expressed in late stage. These marker genes could be used as reference genes of goat follicle GC development. This investigation for the first time discovered the gene expression patterns in goat follicle GCs in high- or low-fertility populations (based on litter size) by scRNA-seq which may be useful for uncovering the oocyte development potential.

Keywords: goat; granulosa cells; litter size; scRNA-seq.

MeSH terms

  • Animals
  • Female
  • Fertility / genetics
  • Gene Expression Profiling
  • Goats / genetics*
  • Granulosa Cells
  • Litter Size / genetics*
  • Ovarian Follicle
  • RNA, Small Cytoplasmic / metabolism

Substances

  • RNA, Small Cytoplasmic