The effect of age and FSH stimulation on the ovarian follicular response, nuclear maturation, and gene expression of cumulus-oocyte complexes in prepubertal gilts.

This study investigated the effects of age and FSH treatment on the ovarian response, follicular fluid (FF) biochemical composition, nuclear maturation, and molecular profile of cumulus-oocytes complexes (COCs) recovered from prepubertal gilts. Thirty-five prepubertal gilts were separated according to age [140 (n = 20) or 160 (n = 15) days], and within each age, the gilts were allotted to receive either 100 mg of FSH [treated; G140+FSH (n = 10) and G160+FSH (n = 7)] or saline solution [control; G140+control (n = 10) and G160+control (n = 8)]. Thus, four experimental groups were included in this study. In the FSH-treated gilts, the percentage of medium follicles increased (P < 0.0001) in the same proportion with which the percentage of small follicles decreased (P < 0.0001). In addition, the glucose concentration in the FF obtained from medium follicles increased (P < 0.05), while that of triglycerides decreased (P < 0.05) in the FSH-treated gilts. The FSH stimulation also improved (P < 0.05) the number of grade I COCs obtained from medium follicles and the meiotic maturation and BCB + rates. FSH treatment only upregulated (P < 0.05) HMGCR expression in immature COCs from prepubertal gilts. The metaphase II and BCB + rates, FF glucose and plasma IGF-1 levels were greater (P < 0.05) in prepubertal gilts at 160 than at 140 days of age. Age had no effect (P > 0.05) on the transcript abundance of the target genes in immature COCs. Hence, oocytes obtained from 140-day-old prepubertal gilts appeared less meiotically competent than those of 160-day-old prepubertal gilts. Our study suggests a possible strategy of using FSH treatment to improve oocyte quantity, quality, and nuclear maturation in 140 and 160-day-old prepubertal gilts.

Investigating pig survival in different production phases using genomic models.

Pig survival is an economically important trait with relevant social welfare implications, thus standing out as an important selection criterion for the current pig farming system. We aimed to estimate (co)variance components for survival in different production phases in a crossbred pig population as well as to investigate the benefit of including genomic information through single-step genomic best linear unbiased prediction (ssGBLUP) on the prediction accuracy of survival traits compared with results from traditional BLUP. Individual survival records on, at most, 64,894 crossbred piglets were evaluated under two multi-trait threshold models. The first model included farrowing, lactation, and combined postweaning survival, whereas the second model included nursery and finishing survival. Direct and maternal breeding values were estimated using BLUP and ssGBLUP methods. Furthermore, prediction accuracy, bias, and dispersion were accessed using the linear regression validation method. Direct heritability estimates for survival in all studied phases were low (from 0.02 to 0.08). Survival in preweaning phases (farrowing and lactation) was controlled by the dam and piglet additive genetic effects, although the maternal side was more important. Postweaning phases (nursery, finishing, and the combination of both) showed the same or higher direct heritabilities compared with preweaning phases. The genetic correlations between survival traits within preweaning and postweaning phases were favorable and strong, but correlations between preweaning and postweaning phases were moderate. The prediction accuracy of survival traits was low, although it increased by including genomic information through ssGBLUP compared with the prediction accuracy from BLUP. Direct and maternal breeding values were similarly accurate with BLUP, but direct breeding values benefited more from genomic information. Overall, a slight increase in bias was observed when genomic information was included, whereas dispersion of breeding values was greatly reduced. Combined postweaning survival presented higher direct heritability than in the preweaning phases and the highest prediction accuracy among all evaluated production phases, therefore standing out as a candidate trait for improving survival. Survival is a complex trait with low heritability; however, important genetic gains can still be obtained, especially under a genomic prediction framework.

Expression of apoptosis and myogenesis related genes during prenatal life in two divergent breeds of pigs.

We aimed to evaluate apoptosis and myogenesis related genes expression in embryos and fetuses from two divergent genetic groups of pigs: Piau breed and a commercial line. Thirty females (15 Piau and 15 commercial line) were selected at 120 days of age. Estrous cycle was observed and on the third estrus females were considered sexually mature. Gilts were inseminated with semen from males of the respective breed. Three females from each breed were slaughtered at five different gestational ages: 15, 30, 45, 60 and 90 days. Whole embryos (15 and 30 d) and samples of longissimus dorsi muscle from fetuses (45, 60 and 90 d) were collected for RNA extraction. Expression of apoptosis and myogenesis related genes (BAX, BCL2, FGF4, IHH, HHIP, SHH, SOX2, WNT1 and WNT4) were evaluated by quantitative real time PCR. There was significant effect of interaction between breeds and gestational ages for all genes evaluated (P < 0.05). The BCL2 gene expression differed throughout pregnancy in Piau group with lower expression on day 15. The IHH gene expression throughout pregnancy was lower on days 15 and 60 in Piau group and lower on day 90 in commercial line group; and the SHH gene expression throughout pregnancy was higher on day 30 and lower on day 60 in Piau group and lower on day 45 in commercial group. The WNT1 gene expression along pregnancy was lower on day 15 and higher on days 30 and 45 in Piau group, and it was higher on day 30 than days 15 and 60 in commercial group. WNT4 gene expression throughout pregnancy was lower on day 15 in Piau group, and it was lower on day 30 in commercial pigs. Piau group presented higher expression of the FGF4 gene on days 45, 60 and 90, and commercial group showed higher expression on day 15 and 90. SOX2 gene expression was lower on day 15 in Piau pigs and it was constant throughout pregnancy in commercial group. Overall, the expression of IHH, SHH, WNT1, WNT4 and FGF4 genes were higher in commercial than Piau pigs on day 15, besides expression of BCL2 gene in Piau embryos was lower on day 15; these results might indicate that the muscle precursor cells are allowed to proliferate for a longer time in commercial than in Piau embryos by the balance of proliferative and apoptotic genes. Therefore, the expression differential between breeds can stimulate proliferation and differentiation of cells in different ways, explaining the postnatal differences in the muscularity between pigs from Piau breed and a commercial line.

Effects of heterozygosity on performance of purebred and crossbred pigs.

BACKGROUND: In pigs, crossbreeding aims at exploiting heterosis, but heterosis is difficult to quantify. Heterozygosity at genetic markers is easier to measure and could potentially be used as an indicator of heterosis. The objective of this study was to investigate the effect of heterozygosity on various maternal and production traits in purebred and crossbred pigs. The proportion of heterozygosity at genetic markers across the genome for each individual was included in the prediction model as a fixed regression across or within breeds. RESULTS: Estimates of regression coefficients of heterozygosity showed large effects for some traits. For maternal traits, regression coefficient estimates were always in a favourable direction, while for production, meat and slaughter quality traits, they were both favourable and unfavourable. Traits with the largest estimated effects of heterozygosity were total number born, litter weight at 3 weeks, weight at 150 days, and age at 40 kg. Estimates of regression coefficients on heterozygosity differed between breeds. Traits with the largest effect of heterozygosity also showed a significant (P < 0.05) increase in prediction accuracy when heterozygosity was included in the model compared to the model without heterozygosity. CONCLUSIONS: For traits with the largest estimates of regression coefficients on heterozygosity, the inclusion of heterozygosity in the model improved prediction accuracy. Using models that include heterozygosity would result in selecting different animals for breeding, which has the potential to improve genetic gain for these traits. This is most beneficial when crossbreds or several breeds are included in the estimation of breeding values and is relevant to all species, not only pigs. Thus, our results show that including heterozygosity in the model is beneficial for some traits, likely due to dominant gene action.