The quality of porcine oocytes for use in IVF is commonly graded according to the number of layers of cumulus cells (CCs) surrounding the oocyte; together these form the cumulus oocyte complex (COC). At least three compact layers of CCs is regarded as important for efficient IVP. To test this, oocytes were scored according to cumulus investment, with grade A representing COCs with three or more cumulus layers including granulosa cell‐cumulus oocyte complexes, grade B those with an intact corona radiata surrounded by another layer of cumulus cells and grades C and D representing COCs with lower CC investment. These oocytes were then monitored for in vitro maturation (IVM), as assessed by tubulin immunostaining for meiotic progression, the development of a cortical granule ring, and by glutathione levels. Results indicate that grading correlates closely with nuclear maturation and cytoplasmic maturation, suggesting that grading oocytes by cumulus investment is a reliable method to predict IVM success. Importantly, Grade A and B oocytes showed no significant differences in any measure and hence using a cut‐off of two or more CC layers may be optimal. We also determined the effect of assisted aspiration for oocyte retrieval, comparing the effect of needle size and applied pressure on the retrieval rate. These data indicated that both variables affected oocyte recovery rates and the quality of recovered oocytes. In combination, these experiments indicate that grade A and B oocytes have a similar developmental potential and that the recovery of oocytes of these grades is maximised by use of an 18‐gauge needle and 50 mmHg aspiration pressure.

The study of pig preimplantation embryo development has several potential uses: from agriculture to the production of medically relevant genetically modified organisms and from rare breed conservation to acting as a physiologically relevant model for progressing human and other (e.g., endangered) species’ in vitro fertilisation technology. Despite this, barriers to the widespread adoption of pig embryo in vitro production include lipid-laden cells that are hard to visualise, slow adoption of contemporary technologies such as the use of time-lapse incubators or artificial intelligence, poor blastulation and high polyspermy rates. Here, we employ a commercially available time-lapse incubator to provide a comprehensive overview of the morphokinetics of pig preimplantation development for the first time. We tested the hypotheses that (a) there are differences in developmental timings between blastulating and non-blastulating embryos and (b) embryo developmental morphokinetic features can be used to predict the likelihood of blastulation. The abattoir-derived oocytes fertilised by commercial extended semen produced presumptive zygotes were split into two groups: cavitating/blastulating 144 h post gamete co-incubation and those that were not. The blastulating group reached the 2-cell and morula stages significantly earlier, and the time taken to reach the 2-cell stage was identified to be a predictive marker for blastocyst formation. Reverse cleavage was also associated with poor blastulation. These data demonstrate the potential of morphokinetic analysis in automating and upscaling pig in vitro production through effective embryo selection.

Artificial insemination (AI) is commonplace in commercial pig breeding, and as such, ensuring sperm sample quality is of utmost importance to avoid reduced farrowing rates and litter sizes. Here, we have used high-throughput nuclear morphometric analysis to compare pig sperm samples categorised as meeting the AI standard (AIS) or not meeting the AI standard (N-AIS). We find that pig sperm nuclei are asymmetric, and that samples contain phenotypic shape abnormalities that show continuous variation. Samples classed as N-AIS have more abnormally shaped sperm than AIS samples, but conventional analysis misses many. The specific phenotypes identified suggest aspects of spermiogenesis that may be disrupted and indicate future avenues for improving pig sperm quality. This method reveals a significant difference in sperm head morphology between AIS and N-AIS pig sperm samples and has the potential to be further developed as a high-throughput tool for sperm head morphology assessment both in the pig breeding industry and in other species.

Artificial insemination (AI) is commonplace in commercial pig breeding, and as such, ensuring sperm sample quality is of utmost importance to avoid reduced farrowing rates and litter sizes. Here, we have used high-throughput nuclear morphometric analysis to compare pig sperm samples categorised as meeting the AI standard (AIS) or not meeting the AI standard (N-AIS) (50 vs. 44 samples from unique boars, respectively). We show that pig sperm nuclei are asymmetric, that samples contain phenotypic shape abnormalities that show continuous variation and that samples classed as N-AIS have more abnormally shaped sperm than AIS samples. This variation is not detected in conventional analysis. The specific phenotypes identified suggest the disruption of key aspects of spermiogenesis and indicate future avenues for improving pig sperm quality. Additionally, we find that the distribution and severity of abnormal sperm phenotypes were significantly associated with the day of semen collection, indicating that environmental factors may influence sperm morphology. High-throughput nuclear morphometric analysis therefore reveals significant differences in sperm head morphology between AIS and N-AIS pig sperm samples and has the potential to be further developed as a tool for sperm assessment both in the pig breeding industry and in other species.