From follicle pool to piglet birth weight (variation)

Introduction

As the economic success of sow husbandry relies very much, but not solely, on the ability of sows to produce a high number of piglets per sow per year, a high sow litter size contributes to this goal. Genetic selection for higher litter size has resulted in a steady increase in sow litter size in the last decades, and this increase in litter size still continues. For example, in the Netherlands, sow litter size (total number born) has increased from 11.6 in 1996 to 13.3 in 2006 and 15.8 in 2016 (Agrovision, 2016). Concomitantly with this increase in total number born of about 0.2 piglets per year, however, also the number of stillborn piglets has increased (from 0.7 to 1.2 piglets) and so did the percentage of piglets that died during lactation (from 11.5% to 14.3%). Similar trends are seen in Denmark between 1996 and 2011, where litter size increased from 11.2 to 14.8, but not in the UK where live born litter size only increased by 0.6 piglet to 11.4 in those 16 years (Rutherford et al., 2013).

These higher litter sizes have consequences for both sow and piglet physiology, welfare and performance, as has been extensively reviewed (Rutherford et al., 2013, Baxter et al., 2013). In this paper, we will focus on the relations between litter size and piglet birth weight and birth weight variation, as these are indicative for subsequent piglet performance. We discuss the potential physiological background of these relations and incorporate findings of recent PhD studies on this topic at Wageningen University (Da Silva, 2018, Costermans, 2020). Finally, we discuss some breeding and management conditions affecting these litter characteristics (reviewed in Kemp et al., 2018).

Litter characteristics

Larger litters have on average lower piglet birth weights and more variation in piglet birth weight within litters (Quesnel et al., 2008). For example, in organic sows with an average litter size of 17.4±0.3 piglets, Wientjes et al., (2012b) found that each extra piglet in the litter was related with a 40 g lower average piglet birth weight, a 0.75% increase in the variation coefficient in birth weights within a litter and a 1.5 % increase in the percentage of piglets with a birth weight of less than 800 g. These relations between litter size and litter characteristics also have a genetic background, as negative genetic correlations are found between litter size and birth weight (-0.30 to -0.49), and positive genetic correlations between litter size and variation in birth weight (0.21 to 0.25) and pre-weaning mortality (0.25 to 0.45) (reviewed by Da Silva, 2018).

This lower average piglet birth weight and higher variation in piglet birth weights are relevant because of the increased chances of mortality during lactation of the lower birth weight piglets. This increased mortality is related with impaired energy reserves and thermoregulatory capacity, delayed and reduced colostrum intake and a disadvantage in competing with heavier littermates at the udder (Milligan et al., 2002, Damgaard et al., 2003, Quesnel et al., 2012). Moreover, lower average birth weight negatively affects growth performance and carcass quality of the piglets that survive (Beaulieu et al., 2010, Rehfeldt et al., 2008).

So, what causes the association between litter size and piglet birth weight (variation)?

Physiological background

Ovulation rate

Litter size is determined by underlying physiological processes like ovulation rate, oocyte fertilisation rate and embryo and foetal survival and development. Ovulation rates (as found in sow and gilt experiments all over the world in the last 36 years, reviewed by Da Silva (2018), have increased by approximately 0.2 ovulations per year, in sows as well as in gilts (see Figure 1). The variation in ovulation rate between sows can be quite considerable, e.g. varying from 17 to 49 in a group of 91 multiparous sows (Da Silva, 2018) (see Figure 2). Thus, higher litter sizes have come with high average ovulation rate, but also with extremely high ovulation rates in some sows.

Figure 1. Ovulation rate as found in studies during the last 35 years, showing an increase of 0.2 ovulations per year in both gilts and sows (Da Silva, 2018).

Figure 2. Variation in ovulation rate in multiparous sows (based on Da Silva, 2018).

Pre-natal survival and development

When sows are inseminated at the right time with good quality semen, fertilisation rate is considered to be 90-100% (reviewed by Kemp and Soede, 1997). A higher ovulation rate results in more implanting embryos. Each embryo needs a certain amount of uterine space to develop a placenta of sufficient length to sustain its development, growth and survival. Insufficient uterine space will result in increased embryonic and foetal mortality, and will also limit foetal development, a phenomenon that is called uterine crowding (Foxcroft, et al., 2014). This phenomenon has been eloquently demonstrated in an experiment (Père et al., 1997) in which surgical Unilateral-Ovary-Hysterectomy (UHOX) was performed to decrease uterine space per embryo (thus inducing higher levels of uterine crowding), while at the same time in another group of sows surgical ligation of one oviduct was performed to increase uterine space per embryo (thus decreasing the level of uterine crowding). As a result, the ovulation rate per uterine horn varied from 4.3 (ligation) to 8.7 (control) and 17.0 (UHOX), corresponding to the ranges of ovulation rate per uterine horn (Figure 2). These differences in ovulation numbers corresponded to differences in pre-natal survival at day 112 of pregnancy, prenatal weight and placental weight as expected in low vs. high crowding situations (Père et al., 1997).

That current high ovulation rates indeed affect embryo survival and embryo quality as has recently been corroborated by Da Silva et al. (2016) and Da Silva et al. (2017a) for sows and gilts, respectively. Figure 3 shows the increased gap between ovulation rate and number of embryos at day 35 of pregnancy, in both sows and gilts exhibiting a high ovulation rate. This gap is due to increased levels of early mortality (the gap between the number of ovulated follicles and total number of embryos) and late embryo mortality (the number of non-vital and degenerated embryos). Moreover, in gilts (Da Silva et al., 2017a) high ovulation rates were related with higher within litter variation in birth weight (ß=0.01). In sows, high ovulation rates were related with lower placental lengths, where each additional corpus luteum (CL) represented a decrease in placental length of 0.38 cm at day 35 of pregnancy. This decrease in placental length was, not surprisingly, associated with increased late embryo mortality (Da Silva et al., 2016).

Figure 3. Relation between ovulation rate and the predicted number of total (thick line) and vital (this line) embryos at day 35 of pregnancy in sows and gilts. The dashed line (- - -) represents the potential number of embryos (i.e. ovulation rate) (Da Silva, 2017). Note: The difference between total and vital embryos is considered to be late embryonic mortality and the difference between ovulation rate and total number of embryos is considered to be early mortality.

Relation between ovulation rate and the predicted number of total (thick line) and vital (this line) embryos at day 35 of pregnancy in sows and gilts. The dashed line (- - -) represents the potential number of embryos (i.e. ovulation rate) (Da Silva, 2017). Note: The difference between total and vital embryos is considered to be late embryonic mortality and the difference between ovulation rate and total number of embryos is considered to be early mortality.

Da Silva et al. (2018) related estimated breeding values (EBVs) for litter size (Topigs Norsvin, Vught, The Netherlands) to ovarian and embryonic characteristics of gilts at day 35 of pregnancy (see Table 1). In these gilts, an increase in one unit of EBV for litter size (i.e. one piglet) was related with a 1.12 increase in ovulation rate. There were no indications found that embryonic or placental characteristics were negatively related with EBV at this stage of pregnancy. Therefore, in these gilts, embryonic-placental units do not seem to be compromised at day 35 of pregnancy. It should be noted, however, that this group of gilts had a relatively high level of early embryo mortality, related with the used semen age, which may have negated potential negative effects of high ovulation rates on the embryonic placental units.

Table 1. ß-estimates of the relations between estimated breeding values of gilts for total number of piglets born (EBV TNB), average piglet birth weight (EBV BW) and within litter piglet birth weight standard deviation (EBV BWSD) and ovarian and embryonic characteristics at 35 days of pregnancy (based on (Da Silva et al., 2018)

ß-estimates of the relations between estimated breeding values of gilts for total number of piglets born (EBV TNB), average piglet birth weight (EBV BW) and within litter piglet birth weight standard deviation (EBV BWSD) and ovarian and embryonic characteristics at 35 days of pregnancy (based on (Da Silva et al., 2018)

In the same study, (Da Silva et al., 2018) analysed associations between EBVs for piglet birth weight and within litter variation in piglet birth weight with ovarian and embryonic characteristics at day 35 of pregnancy. The EBVs did not appear to be related with ovulation rate; so, selection for a higher piglet birth weight and lower within litter variation in piglet birth weight did not affect ovulation rate. Interestingly, both the EBV for piglet birth weight and for within-litter variation in piglet birth weight had a strong positive association with another ovarian characteristic, namely average CL weight at day 35 of pregnancy (see Table 1).

In another study, Da Silva et al. (2017b) used transrectal ultrasound (TUS) to assess the average diameter of the 10 largest CL (5 per ovary) at day 20-30 of pregnancy, and related this to subsequent piglet birth weight and standard deviation in piglet birth weight (see Figure 4). Each extra mm in CL diameter was related with an increase in average piglet birth weight of 36 g and a standard deviation in piglet birth weight of 24 g. Moreover, an increase in EBV for litter size was related to lower CL weights (Da Silva et al., 2018)). Collectively, these data indicate that the selection for litter size resulted in smaller CL during pregnancy, which again is related to lower birth weights.

Figure 4. Effect of average CL diameter measured using transrectal ultrasound (TUS) at ~ day 30 of pregnancy [5.5 to 7.8 mm (n = 23); 7.9 to 8.9 mm (n = 47); and 9.0 to 10.5 mm (n = 30)] on BW of total piglets born [P = 0.04; corrected for litter size class P < 0.0001] (panel A) standard deviation (SD) of BW of the total piglets born (P = 0.02) (panel B). ^ab P< 0.05. LSM±SE (from Da Silva et al., 2017b).

Effect of average CL diameter measured using transrectal ultrasound (TUS) at ~ day 30 of pregnancy [5.5 to 7.8 mm (n = 23); 7.9 to 8.9 mm (n = 47); and 9.0 to 10.5 mm (n = 30)] on BW of total piglets born [P = 0.04; corrected for litter size class P < 0.0001] (panel A) standard deviation (SD) of BW of the total piglets born (P = 0.02) (panel B). ab P< 0.05. LSM±SE (from Da Silva et al., 2017b).

The next question that arises is: What could be the physiological mechanism explaining the relation between CL weight and litter characteristics? Average CL weight and variation in CL weight are positively correlated; so, a higher average CL weight is accompanied by more variation in the CL pool. As CL size has been related to the size of the pre-ovulatory follicles (e.g. Wientjes et al., 2012a), it is of interest to explore the possible contribution of these follicles on piglet birth weight (variation).

Pre-ovulatory follicle pool

The CL pool originates from follicles that are recruited from the antral follicle pool at weaning when the suppression of the hypothalamic-pituitary axis is released, and gonadotropin levels increase to simulate recruitment of small antral follicles to develop into dominant and ovulatory follicles. Considerable heterogeneity in size, morphology and endocrine status is seen in the pre-ovulatory follicles of gilts during oestrus (Hunter and Wiesak, 1990, Knox, 2005). The maturation of the oocyte within the follicle is highly dependent of the synthesis of steroid and (growth) factors by the surrounding granulosa and theca cells, as well as nutrients and hormones from the blood circulation. These all contribute to the composition of the follicular fluid. Extensive direct contact between the cumulus granulosa cells and the oocyte and exchange of metabolic intermediates further contribute to oocyte maturation and competence (from Costermans, 2020).

The heterogeneity in follicular (and oocyte) development and concomitant competence at ovulation has been related with variability in early embryonic development and subsequent mortality of the less developed embryos (Pope et al., 1990, Xie et al., 1990). Larger follicles (and thus larger CL (e.g. Wientjes et al., 2012a), may therefore represent better competent follicles at ovulation that release higher quality oocytes (Marchal et al., 2002) that develop into better quality embryos. Indeed, at day 35 of pregnancy, a higher average CL weight was related with a higher vital embryo weight (r=0.17) and a higher vital implantation length (r=0.24) (Da Silva et al., 2018).

Thus, the association between CL size and piglet birth weight may find its origin in the association between follicle development and oocyte competence at ovulation. That this indeed might be the case is supported by studies in which insulin-stimulating diets during the period of antral follicle development, i.e. lactation and/or the weaning-to-estrus interval (Van den Brand et al., 2006, Van den Brand et al., 2009) and weight losses during lactation (Wientjes et al., 2013) affected piglet birth weight and within-litter birth weight variation of the subsequent litter.

Recent studies in the PhD project of Natasja Costermans (Costermans, 2020) increased our understanding of early post-weaning follicle development. The aim of her thesis was to determine the parameters that determine follicular competence (i.e. the competence to release good quality oocytes) which may thereby contribute to piglet birth weight (variation). The first step in the thesis work was an attempt to relate the estimated breeding value for birth weight variation (EBV-LVR) of parity 3-5 sows to follicle development at weaning (Costermans et al., 2019c). Unfortunately, it was not possible to create a large contrast in EBV-LVR between the animals and no relations were found with follicle size or follicle variation. So, currently, direct information on relations between sow breeding values for birth weight variation and follicle pool characteristics is lacking.

To get a better understanding of the characteristics that determine follicular competence, follow-up studies investigated gene and protein expression of granulosa cells and follicular fluid composition in dependence of follicle size, follicle health (as determined by using a cleaved Caspase-3 staining of the granulosa cells, a marker for apoptosis) and the quality of the oocytes within the follicles (as determined by the morphology of the cumulus-oocyte-complexes (COCs)). Within the 10 largest healthy follicles on one ovary (the presumptive ovulatory follicle pool), it appeared that the granulosa cells of the smaller follicles expressed more cell proliferation markers and the larger follicles expressed more maturation markers (Costermans et al., 2019a) thus validating that differences in follicle size are related to follicle maturation, also at an early stage of development (at the day of weaning).

Subsequently, relations were studied between follicular fluid steroid profiles and oocyte quality of the presumptive ovulatory follicle pool. Sows with a high (> 70%) compared to low (< 70%) percentage of healthy COCs had higher levels of 17ß-oestradiol, 19-norandostenedione, progesterone and α-testosterone in the follicular fluid, while cortisol levels were lower (Costermans et al. 2019b). Furthermore, the granulosa cells of the sows with the higher percentage of healthy COCs had an increased expression of genes involved in steroidogenesis and follicular maturation. Interestingly, COC-health and follicle size were not related and sows with high vs low follicle size only differed in17ßoestradiol content of the follicle fluid. Thus, at this early stage, not only follicle size, but also COC-health is an indicator of follicle competence.

Interestingly, the sows with a higher percentage of healthy COCs had lost less weight during lactation (7 ± 2 vs 12 ± 2 %) and had higher serum levels of IGF-1 at weaning (167 ± 15 vs 120±16 ng/ml). Surprisingly, differences in average follicle size between the sows were not affected by sow weight loss or IGF-1 levels at weaning, Thus, at this early stage, COC-health may be more affected by lactation energy balance than follicle size.

Relations between sow metabolic state and reproductive parameters are more commonly found in first-litter sows than in older parity sows as young sows that also need energy for growth usually have a lower feed intake capacity and therefore lose relatively more body weight during lactation, with consequent effects on follicle development and performance (e.g. Prunier et al., 2003). Wientjes et al., (2013) found that sows that lost more weight during lactation had higher birth weight variation in the next litter. Therefore, as a next step, follicle development was studied in weaned primiparous sows with different feed allowances during lactation (Costermans et al., 2019d). The sows received increasing amounts of feed up to 5.5 kg at day 9 of lactation and subsequently received either 6.5 kg or 3.25 kg up to day 24, the day of weaning. Follicle development was evaluated 48 h after weaning.

Feed restriction impaired follicle development in primiparous sows, as shown by the lower number of the larger follicles (Fig. 5a) and the reduced average size of the 15 largest follicles (Fig. 5b). It did not affect the percentage of healthy COCs at 2 days after weaning (Fig. 5c), but it did reduce follicle competence to support oocyte development as shown by the reduced COCs expansion after IVM and the reduced fertilisation rate and increased level of polyspermy after IVF of these oocytes (Fig. 5c). These consequences of feed restriction on follicular and oocyte development competence were associated to lower IGF1 levels in the follicular fluid and in serum of these sows.

The mechanisms behind effects of negative energy balance/weight loss on subsequent follicle competence are not entirely clear yet and may dependent on factors such as genotype or feed composition. Clowes et al. (2003) showed that selective protein losses in first litter sows (induced by moderate vs high protein levels in the lactation feed and a standard vs high body mass at parturition) reduced follicle size and follicle fluid oestradiol concentration at weaning. Costermans et al. (2019d) found that average follicle size was negatively associated to both loin muscle depth loss (ß = - 0.85 mm/mm) and back fat loss (ß = -0.22 mm/mm) in the full-fed sows, but not in the feed restricted sows (see Figure 6; Costermans et al., 2019d).

Figure 5. Follicle and oocyte development at 48h after weaning of primiparous sows that were full-fed or restricted-fed during first lactation A: total number of visible antral follicles in different size categories of both ovaries. B: Average follicle size of the 15 largest follicles of both the left and right ovary. C: Oocyte development at 48h and subsequent IVM and IVF results. (Costermans et al., 2019d).

Follicle and oocyte development at 48h after weaning of primiparous sows that were full-fed or restricted-fed during first lactation A: total number of visible antral follicles in different size categories of both ovaries. B: Average follicle size of the 15 largest follicles of both the left and right ovary. C: Oocyte development at 48h and subsequent IVM and IVF results. (Costermans et al., 2019d).

Figure 6. Relations between average follicle size (mm) of the 15 largest follicles of both left and right ovary 48h after weaning and A. Muscle depth loss (mm) during lactation and B. backfat depth loss (mm) during lactation. (Costermans et al., 2019d).

Relations between average follicle size (mm) of the 15 largest follicles of both left and right ovary 48h after weaning and A. Muscle depth loss (mm) during lactation and B. backfat depth loss (mm) during lactation. (Costermans et al., 2019d).

Thus, consequences of not only weight loss, but also specifically protein loss vs back fat loss need to be further evaluated, not only regarding follicle development and subsequent reproductive performance and litter quality, but also in relation to the suckling litter, as body condition losses are also related to milk production of the sow (Clowes et al., 2003; Costermans et al., 2020).

To summarize, higher litter sizes have come with lower piglet birth weights and more variable piglet birth weights, which subsequently are related to compromised post-natal survival and performance of piglets. Two hypotheses have been explored to explain the relation between litter size and (variation in) piglet birth weight; (1) Foetal-placental units are compromised due to uterine crowding, which is more predominant in sows with a high ovulation rate, and (2) selection for litter size has resulted in a more variable quality of the pool of ovulatory follicles. Mechanisms related to metabolic influences on follicle development require further investigation, especially in young sows.

Breeding and management solutions

In breeding programmes, gilts are not selected for only one trait (such as litter size) but for a number of traits that form the breeding goal. Based on the breeding goal, a selection index is created that uses multiple phenotypic traits that are important for the breeding goal (for example, birth weight and birth weight uniformity). Traits in the index receive a value based on their economic weight. Thus, potential negative effects of selection for litter size on (variation in) piglet birth weight or piglet survival are controlled by weighing these parameters (or correlated responses) in the selection index. Indeed, breeding companies have used piglet survival and/or (variation in) birth weight in their selection programs (reviewed by Zak et al. (2017).

Higher litter sizes have been achieved by increased ovulation rates and have resulted in higher levels of uterine crowding. It would be of interest to further investigate the level of uterine crowding (i.e. compromised foetal- placental units) in relation to ovulation rate at different stages of pregnancy. It may also be of interest to consider selection on traits that improve uterine capacity (Freking et al., 2016). Such strategies might not result in improved within-litter birth weight when its cause lies more in the variable pool of follicles at ovulation than in available uterine space. Also, information from Genome-Wide-Association-Studies (GWAS) (Calus, 2010) in such studies could elucidate the genetic background of found relations.

From a management point of view, possibilities to decrease variation in birth weight mostly seem to lie in optimizing nutrition and metabolic state in the early follicular phase. For example, Van den Brand et al., (2006) and Van den Brand et al., (2009) found that insulin-stimulating diets during lactation decreased birth weight variation and Wientjes et al., (2013) found that a higher weight loss during lactation and an increased weaning-to-pregnancy length was associated with subsequent birth weight variation. These effects seemed related with IGF-1 stimulating effects on follicle development. In the studies above, the reduction in birth weight variation seemed only moderate (approximately 2% reduction in coefficient of variation (CV)), but Wientjes et al. (2012b) found that every percent reduction in birthweight CV was related with a 1.08% reduction in early lactation piglet mortality, so also small reductions in variation can have substantial effects on survival. Similarly, each 100g increase in piglet birth weight was found to be related with a 3% decrease in piglet mortality rate.

As far as we know, no nutritional or management strategies during pregnancy have been effective in reducing birth weight variation.

Conclusion

Our knowledge on causes of (variation in) piglet birth weight has increased. We more and more realise that these changes to a certain extent are related to uterine crowding, induced by a higher ovulation rate and affected by the quality of both the ovulating oocytes and remaining corpora lutea. We also observe that there may not be many management options available to influence piglet birth weight (variation), although the follicle pool may be further optimised by creating the right nutritional – metabolic environment during and after lactation.

A point of attention is that relations between metabolic state and reproduction and birth weight are probably dependent on genotype and possibly other factors, which makes it difficult to provide general recommendations.

Published in the proceedings of the International Pig Veterinary Society Congress – IPVS2020. For information on the event, past and future editions, check out https://ipvs2022.com/en.

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From follicle pool to piglet birth weight (variation)

References

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