IDENTIFICATION OF FERTILITY MARKERS IN EQUINE SEMEN USING PROTEOMICS TECHNIQUES
Bibliographic record
Abstract
Current semen evaluation techniques are useful in identifying subfertile animals, however they are not reliable indicators of fertility. As sperm and seminal plasma proteins have known effects on both in vivo and in vitro fertilization, their potential as markers of semen quality and stallion fertility are important areas of research. The objectives of this study were to determine if specific proteins in the stallion semen could be related to semen quality characteristics and in vivo fertility using proteomics techniques. Seven fertile stallions were regularly collected and bred to a total of 142 mares for the 2006 breeding season. Fresh semen for the study was collected on three occasions in the middle of the breeding season (Sandy Ridge Stallion Station, Bassano, Alberta), each two weeks apart, and the sperm and seminal plasma were immediately separated by centrifugation and frozen until subjected to 2D gel electrophoresis. The sperm and seminal plasma proteins were separated on 24 cm 12 % acrylamide gels, and pH 3–10 in the first dimension (GE Healthcare, Baie d'Urfé, QC). All protein species were analyzed and matched across stallions using Progenesis software (Non-Linear Dynamics, Durham, NC). The quantified proteins were compared to visual semen quality characteristics and in vivo fertility using the mixed models procedure with repeated measures as well as correlation analysis in SAS (SAS Institute, Cary, NC). The stallions ranged from 50 % to 100 % for first cycle pregnancy rate, and overall pregnancy rate ranged from 75 to 100 %. When semen quality was assessed, there were differences (P<0.05) in sperm concentration, total number of sperm and semen volume. There were no differences reported in progressively motile sperm (PMS), however there were replicates where stallions showed large variation in their motility, down to 35 % PMS. Only preliminary data has been obtained for the proteomics analysis at this time. Over 3000 proteins for each gel were visualized and quantified using the Progenesis software, and 32 proteins in the spermatozoa and 8 proteins in seminal plasma differed across stallions (P<0.05). For the seminal plasma, 3 proteins were positively correlated with PMS, and 5 were negatively correlated with PMS (P<0.05). Interestingly, none of these proteins were correlated with fertility, however 14 different proteins were either positively or negatively correlated to fertility. For sperm proteins, 3 proteins were positively correlated with PMS and 9 were negatively correlated with PMS (P<0.05). All proteins of interest will be identified and verified using mass spectrometry techniques. Candidate protein markers reported in previous studies, such as osteopontin, will also be characterized in these samples. Subjecting equine sperm and seminal plasma to proteomics techniques has revealed many potential candidates of fertility in both sperm and seminal plasma in preliminary results. Determination of a reliable marker that is associated with stallion fertility would be very useful for screening stallions for breeding potential and also for the improvement of reproductive technologies. (poster)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".