Reproductive efficiency in sows and boars affects the profitability of swine production systems. However, breeding stock selection is primarily based on progeny performance traits such as feed efficiency, growth rate, carcass characteristics, physical appearance, and structure, especially for terminal sire lines, with less emphasis on reproduction. While maternal sire lines are co-selected for reproductive traits including birth litter size, number weaned, weaning weight, and wean to estrus interval, currently, there is no single test predictive of fertility, and thus subfertile males and sub-fertile or even infertile females enter the swine breeding herds (Oh et al., 2006b; Safranski, 2008). Thus, to maximize economic returns and swine production efficiency there is a need for a biomarker to identify boars and gilts with the greatest reproductive potential before admittance into the breeding herd. The overall aim of the described studies was to determine if biomarkers of fertility of boars and gilts could be identified in biological samples taken prior to or just after animals entering the breeding herds using high throughput omic screening tools resulting from recent advancements in mass spectrometry.
Current semen evaluation techniques only identify boars with fertility issues associated with sperm motility, morphology, and concentration. We know that seminal plasma proteins are essential for proper sperm function and play an important role in fertilization. Therefore, we hypothesized that fertility differences could be reflected in the seminal plasma proteome profiles. A fertility index was created from 110 boars with data on total born and farrowing rate following 50 single-sired matings. Thirty-two of the 110 boars were identified as having extreme phenotypes for total born and farrowing rate and were categorized into one of the following: high farrowing rate and high total born (HFHB; n=9), high farrowing rate with low total born (HFLB; n=10), low farrowing rate and low total born (LFLB; n=9), and low farrowing rate with high total born (LFHB; n=4). The seminal plasma proteins were isolated and measured using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). There were 436 proteins measured in at least one sample across all animals, with 245 proteins considered for analysis (detected in samples of at least n=3 animals/phenotype). Of the 245 proteins, 56 were differentially abundant (P < 0.05) between the high fertility phenotype (HFHB) and at least one of the three subfertile groups. Proteins previously associated with fertility such as Porcine seminal protein I (PSP-I) and epididymis-specific alpha-mannosidase (MAN2B2) and free radical detoxification such as superoxide dismutase 1 (SOD1), peroxiredoxin 4 (PRDX4), and glutathione peroxidase 6 (GPX6) were more abundant in HFHB. Subfertile phenotypes had a greater abundance of blood microparticle proteins, biomarkers of inflammation, and lower inositol-1-monophosphatase (IMPA1), which regulates inositol production. Findings supported that seminal plasma protein profiles were distinct between boars with different fertility phenotypes and have the potential to predict boar reproductive performance.
The selection of replacement females for the sow herd is one of the most important facets in sow system management. However, selection of gilts for sow herd replacements is primarily based on how the animal appears such as feet and leg confirmation, the gilt’s underline, and parent past performance. This practice resulted in a high degree of variation in sow reproductive performance traits such as pigs per sow per year (PSY) and increased culling rates due to reproductive failure. In female swine, perinatal nutritional environment has been associated with their long-term fertility. The vaginal lipidome of 2 day and 14 day old gilts was found reflective of nutrition source, which suggests that perinatal nutrition affects the composition of reproductive tissues. Thus, it was hypothesized that the vaginal lipidome profiles of gilts at weaning would be reflective of fertility later in life. The first study aimed to find potential on-farm biomarkers that technicians could use to make selection decisions. Variables chosen as potential biomarkers have potential to influence or predict long-term fertility. Data were prospectively collected from 2146 gilts born on a commercial sow production facility and included birth and weaning weights, vulva length and width at 21 d postnatal (PN), birth and nursing litter size, days nursed, average daily gain from birth to weaning, and age at first estrus. Of the initial animals, 400 (17%) were selected for the sow herd, 353 remained after removing animals culled for non-reproductive reasons. Animals were assigned to 1 of 5 reproductive performance categories based on observation of estrus or pigs per sow per year (PSY) across two farrowings: High Fertility (HF; 23%; n=82; ≥26 PSY), Middle Fertility (MF2; 12%; n=43; 20-25 PSY), Low Fertility (MF3; 15%; n=54; <20 PSY), Infertile-Estrus (IFe; 10%; n= 36; estrus, no pregnancy), and Infertile-No Estrus (IFno; 39%; n=138; no estrus, no pregnancy). Generalized linear model analysis indicated vulva width (P=0.03) was related to PSY, however, it only explained 1.5% of the total variation in PSY. To determine if preweaning variables were predictive of gilt fertility outcome, animals were grouped as those that became pregnant (n=179) or not (n=174). Vulva width tended to be greater in fertile animals versus infertile (P=0.07). Binomial regression analysis revealed a positive relationship between vulva width and gilt fertility; however, this relationship is not strong enough to make sow herd selection decisions.
Because gilts are so phenotypically similar at weaning, we hypothesized that the biomarker predictive of fertility at this stage of selection might need a more sensitive means of detection. Therefore, we evaluated the vaginal lipid profiles from a subset of animals enrolled in the previous study that were the extremes of fertility phenotype: High Fertility (HF; n=28; ≥26 PSY) and Infertile (IF; n=34; no estrus, no pregnancy). Vaginal swabs of the anterior vagina were taken at 21 ± 4 d PN. Lipids were extracted from cellular material collected with swabs and analyzed using multiple reaction monitoring (MRM) profiling for lipidome analysis. Relative abundance of arachidonic acid (ARA, C20:4) and docosahexaenoic acid (DHA, C22:6) were lower (P<0.05) in IF gilts than HF gilts, whereas abundance of the free fatty acids cerotic (C26:0), ximenic (C26:1), and nonadecanoic (C19:0) acids were greater (P<0.05) in IF gilts. Additionally, eicosapentaenoic acid (C20:5), a precursor of prostaglandins, was also higher (P<0.05) in IF gilts.
Previous studies support that higher levels of arachidonic acid in vaginal lipidomes maybe a biomarker of colostrum intake, and thus provides further evidence for a relationship between fertility and the perinatal nutritional environment. The perspective of having a panel of lipids captured with vaginal swabs at weaning that can predict the reproductive efficiency of gilts shows promise and warrants future research in this area. Taken together, the experiments described above demonstrate that detection of infertile and subfertile animals before entering the breeding herd is possible and warrants further development and validation of diagnostic panels capable of doing so.