Conserved and breed-specific differences in the cervical transcriptome of sheep with divergent fertility at the follicular phase of a natural oestrus cycle.

Background: The outcome of cervical artificial insemination (AI) with frozen-thawed semen in sheep is limited by the inability of sperm to traverse the cervix of some ewe breeds. Previous research has demonstrated that cervical sperm transport is dependent on ewe breed, as sperm can traverse the cervix in greater numbers in some higher fertility ewe breeds. However, the molecular mechanisms underlying ewe breed differences in sperm transport through the cervix remain unknown. In this study, we aimed to characterise the cervical transcriptome of four European ewe breeds with known differences in pregnancy rates following cervical AI using frozen-thawed semen at the follicular phase of a natural oestrous cycle. Cervical post mortem tissue samples were collected from two Irish ewe breeds (Belclare and Suffolk; medium and low fertility, respectively) and from two Norwegian ewe breeds (Norwegian White Sheep (NWS) and Fur; high fertility compared to both Irish breeds) at the follicular phase of a natural oestrous cycle (n = 8 to 10 ewes per breed).

Results: High-quality RNA extracted from biopsies of the mid-region of the cervix was analysed by RNA-sequencing and Gene Ontology (GO). After stringent filtering (P <  0.05 and FC > 1.5), a total of 11, 1539 and 748 differentially expressed genes (DEGs) were identified in Belclare, Fur and NWS compared to the low fertility Suffolk breed, respectively. Gene ontology analysis identified significantly enriched biological processes involved in muscle contraction, extracellular matrix (ECM) development and the immune response. Gene co-expression analysis revealed similar patterns in muscle contraction and ECM development modules in both Norwegian ewe breeds, which differed to the Irish ewe breeds.

Conclusions: These breed-specific biological processes may account for impaired cervical sperm transport through the cervix in sheep during the follicular phase of the reproductive cycle. This novel and comprehensive dataset provides a rich foundation for future targeted initiatives to improve cervical AI in sheep.