Skip to main content
NCBI home page
Springer logoLink to Springer
. 2026 Mar 20;67(2):487–501. doi: 10.1007/s13353-026-01046-x

Evaluation of pedigree structure, inbreeding levels, and inbreeding depression in reproduction traits in two Polish Złotnicka native pig breeds

Natalia Pycińska 1, Karolina Szulc 2, Ewa Sell-Kubiak 1,✉
PMCID: PMC13079468  PMID: 41857340

Abstract

This study aimed to assess the pedigree structure, estimate the level of inbreeding, and determine its impact on reproductive traits in two native Polish pig breeds covered by genetic resource conservation programs: Złotnicka White (ZW) and Złotnicka Spotted (ZS). The inbreeding coefficient was estimated using the classical Wright’s method and, for the first time, in those breeds, the modified VanRaden’s method, which accounts for incomplete pedigree information. The analysis included pedigree data collected between 1953 and 2021 for 6,126 ZW and 5,934 ZS individuals. The average inbreeding coefficients for the ZW breed were 9.97% (Wright) and 26.34% (VanRaden), whereas those for the ZS breed were 9.38% and 21.3%, respectively. In the ZS population, a substantial increase in inbreeding per generation was observed, exceeding the recommended threshold of 1%; i.e. 1.47% using Wright’s method and 1.25% using VanRaden’s method. Effective population size estimates indicated a risk of reduced genetic diversity, particularly according to VanRaden’s method. Further analysis of reproductive traits did not confirm clear or consistent effects of inbreeding depression. In ZW sows, statistically significant but irregular differences were found between inbreeding classes, whereas in ZS pigs, no significant effects were found. Those results should be interpreted with caution, given the incomplete pedigree information available for part of the population. Overall, the effect of inbreeding on the number of piglets born alive and surviving to 21 days was weak and of limited biological relevance. The results emphasise the need for intensified measures to control the increase in inbreeding and to maintain genetic diversity in these native pig populations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13353-026-01046-x.

Keywords: Złotnicka White pigs, Złotnicka Spotted pigs, Inbreeding depression, Inbreeding coefficient, Pedigree analysis, Native pig breed

Introduction

A high level of homozygosity in native pig breeds is associated with the mating of closely related individuals. This is caused by a small population size, and their breeding is concentrated mainly on small farms covered by genetic resource conservation programs (de Oliveria et al., 2022). This reduces the number of breeding animals, increasing the chances of inbreeding. Consequently, this may lead to the expression of harmful mutations (Charlesworth and Willis 2009) and a decline in genetic variability within the population (Sell-Kubiak et al. 2018). A notable consequence of this phenomenon is a decrease in both production and reproductive performance in animals with an increased inbreeding coefficient, referred to as inbreeding depression (Lush 1945; Falconer and Mackay 1996; Silió et al. 2016; de Oliveria et al., 2022; Zhang et al. 2022). In pigs, a negative correlation has been observed between the inbreeding coefficient and the average daily gain before weaning (de Oliveria et al., 2022), as well as for traits such as the total number of piglets born (TNB), the number of live-born piglets (NBA), and the litter birth weight (Zhang et al. 2022). The inbreeding coefficient measures the probability that an individual shares alleles that are identical by descent from common ancestors (Wright 1922; Malécot 1948; Koenig and Simianer 2006). One classical approach to estimate this parameter is based on pedigree information, which provides the expected probability that two alleles are identical by descent (IBD) (Wright 1922; Malécot 1948; Saura et al. 2015). However, a major challenge of this approach is the often limited availability of deep pedigree records and gaps within them. In cases where the pedigree lacks information on ancestors or includes only one parental line, the best method for estimating inbreeding is the one proposed by VanRaden (1992). This method involves determining the average inbreeding level for a given birth year and then using it to estimate the inbreeding coefficient of the offspring.

The Poznan University of Life Sciences maintains herdbooks for two native Polish pig breeds: Złotnicka Spotted and Złotnicka White. The pedigrees for these breeds date back to the 1950s. Although several studies investigated inbreeding levels in these breeds (e.g., Szulc et al. 2006; Szyndler-Nędza 2013, 2014), they have primarily relied on the Meuwissen and Luo algorithms, which do not account for missing parental records. Szmatoła et al. (2020) estimated genomic inbreeding coefficients derived from runs of homozygosity (ROH), which is the most accurate method; however, they did not evaluate the inbreeding depression in reproductive traits. To date, only two studies have analysed inbreeding depression in reproductive traits in Złotnicka breeds (Szulc et al. 2006; Szyndler-Nędza et al., 2014). Those studies used an inbreeding coefficient estimated without accounting for missing parental information and applied analysis on a much-reduced subset of Złotnicka breeds data.

Thus, this study aimed to analyze pedigree data, estimate the inbreeding coefficient with VanRaden’s and Wright’s methods, and assess the effects of inbreeding depression on reproductive traits over time in two native Polish Złotnicka pig breeds.

Materials and methods

Pedigree data

Pedigree data from herdbooks of the two Złotnicka pig breeds (Złotnicka White - ZW, and Złotnicka Spotted - ZS) collected between 1953 and 2021 were used for the analysis. The general pedigree structure for both breeds is summarized in Table 1.

Table 1.

The summary of pedigree structure as an overview of the available genealogical information for Złotnicka White and Złotnicka Spotted breeds

Złotnicka White Złotnicka Spotted
Number of animals 6,126 5,934
Number of founders 125 195
Mean traced generations 29.16 21.17
Max traced generations 43 35
Open in a new tab

For ZW, the initial dataset included 6,535 individuals. However, Four hundred nine individuals were excluded due to missing birth dates, which could not be estimated based on progeny data; these individuals did not have offspring in the subsequent pedigree generations. After editing, 6,126 individuals remained, among which 461 boars and 2,061 sows were identified as known parents within the pedigree.

In the case of ZS, the original pedigree contained 6,420 individuals; after removing 486 pigs with missing or non-estimable birth years, 5,934 individuals remained. Among them, 479 boars and 1,909 sows were recognized as parents. The year of birth was available or successfully assigned for all the animals included in the final dataset. When the birth year was missing, it was estimated based on the birth year of the oldest offspring present in the dataset, assuming that the parent was at least one year older than its oldest progeny (VanRaden 1992; Aguilar and Misztal 2008; Sell-Kubiak et al. 2018). This allowed the estimation of inbreeding levels by year of birth.

Defining the base year

The method for estimating inbreeding proposed by VanRaden (1992) assumes the use of a base year in analyses of this parameter when parental information is incomplete. This strategy helps to avoid overestimating inbreeding relative to the year of birth, especially in cases where only a small number of animals have known ancestry during the early stages of population formation. For both breeds, 1953 was adopted as the base year, as it marks the point when all pigs were gathered at the Experimental Teaching Station in Złotniki near Poznań, which belonged to the then-called Agricultural Academy in Poznań. This event represented a key moment of consolidation for breeding both Złotnicka breeds (Szulc et al. 2021a, b). Defining the base year allowed the pedigree to be edited according to the following assumption (VanRaden 1992; Sell-Kubiak et al. 2018):

  1. An individual’s parents born before 1953 were considered unrelated and noninbred;

  2. Animals born before 1953 were retained only if they had at least two offspring born after that year;

  3. The first generation born after 1953 was considered related but assumed not to be inbred;

  4. From the second post-1953 generation onwards, increasing levels of relatedness and inbreeding were expected and estimated.

Calculation of pedigree completeness

An important parameter in estimating the inbreeding coefficient is pedigree completeness. The Pedigree Completeness Index (PCI) was calculated based on five generations, following the method proposed by MacCluer et al. (1983), using the following formula:

graphic file with name d33e420.gif

where Cf and Cm are defined as the proportions of known ancestors on the paternal and maternal sides of the pedigree, respectively. These parameters were estimated using the formula:

graphic file with name d33e432.gif

where ​ ai is the proportion of known ancestors in the i-th generation, and d is the number of generations considered.

Pedigree depth analysis

To determine the pedigree depth, one of the three standard indicators described by Gutiérrez and Goyache (2005) - the maximum number of generations traced — was used. This parameter represents the maximum number of generations separating an individual from its most distant known ancestor. It was calculated using the countGen() function implemented in the pedigree package in RStudio (Coster 2022), which follows the same computational principle as that used in the ENDOG software (Gutiérrez and Goyache 2005). The average number of traced generations was then obtained for each breed to describe the overall pedigree depth.

Estimation of the inbreeding coefficient

Two methods were used to estimate inbreeding levels for each year based on the pedigrees of the Złotnicka breeds. The first method was based on the classical Wright’s (1922) approach, whereas the second method followed the modification proposed by VanRaden (1992). The adjustment assumes that individuals with unknown ancestry are assigned the average inbreeding rate for their birth year, as described by Sell-Kubiak et al. (2018). The algorithm published by Aguilar and Misztal (2008), embedded in the Inbupgf90 software, was used for the calculation. The procedure consisted of several steps. First, the inbreeding coefficient was estimated according to the formula of Emik and Tereill (1949):

graphic file with name d33e474.gif

where Rsd represents the coefficient of the relationship between the father (s) and the mother (d).

Initially, the algorithm temporarily assigned an inbreeding ancestry value of zero to animals with unknown ancestry. The mean inbreeding level per birth year was calculated, and in subsequent iterations, this mean was reassigned to animals previously marked as unknown until convergence was reached. The recursive algorithm analyzes previous generations and computes the relationship coefficient between an individual’s parents (Aguilar and Misztal 2008). Finally, the average inbreeding level for a given year was assigned to individuals with a known birth year but lacking complete pedigree information (VanRaden 1992).

Estimation of the effective population size

The effective population size (Ne) is the size of an idealised population that would experience the same rate of loss of genetic variation, through genetic drift and inbreeding, as the real population. Here, following Gutiérrez et al. (2008), we use the adjusted effective population size (Inline graphic) accounting for the one-generation delay in the expression of inbreeding:

graphic file with name d33e503.gif

where Inline graphic is the average of individuals’ inbreeding rate in the population. To calculate Inline graphic, a correction was applied, as suggested by Gutiérrez et al. (2009):

graphic file with name d33e519.gif

where Fi is the individual’s inbreeding coefficient (from Wright or VanRaden method), and ti is the equivalent complete generation number to which the individual belongs. Ne estimates were based only on animals with a pedigree completeness index value (PCI; MacCluer et al. 1983) of 0.9 or greater. This assumption was made, since values below 0.9 have been reported to introduce bias in inbreeding and Ne estimates due to incomplete pedigree information (Boichard et al. 1997).

Statistical analysis of the impact of inbreeding depression on reproductive traits

Records of two reproductive traits (number born alive - NBA and number alive at 21 days – NA21) were available in Złotnicka sows born from 2000 onwards, as presented by Sell-Kubiak et al. (2025). In total, 3876 ZW sows with 21,368 litters and 3375 ZS sows with 17,600 were available for analysis. Each sow had at least two litters recorded (average 5.5 litters/sow in ZW and 5.2 litters/sow in ZS), including the first parity, with younger sows having a lower number of records. The distribution of records per sow is presented in the Supplementary material (Figure S1). Here, the average NBA and NA21 per sow was used to simplify the analysis. To verify the significance of inbreeding depression on reproductive traits in both breeds, an Animal model for mean NBA and mean NA21 used previously by Sell-Kubiak et al. (2025), was applied. The fixed effects in the model were: farm where the sow gave birth to piglets for the first time, the combination of the year and the season of the sow’s first farrowing. The addition to that model included the inbreeding level of the sow, obtained using two methods: Wright’s or VanRaden’s. The inbreeding level was included in the model either as a continuous (linear) or categorical (class) variable. The analysis were run in ASReml 4.2 (Gilmour et al. 2015). The following linear models were used for both breeds:

graphic file with name d33e557.gif

where y is the mean of the trait (NBA or NA21) for the sow; X and Z are incidence matrices linking levels of fixed and random effects with observations y; b is a vector of fixed effects; Inline graphic is a vector of additive genetic effects, with Inline graphic, where Inline graphic is the augmented numerator relationship matrix and Inline graphic is the additive genetic variance; Inline graphic is a vector of residuals, with Inline graphic, where Inline graphic is the appropriate identity matrix and Inline graphic is the residual variance; and Inline graphic and Inline graphic are independent.

The model included weights on the phenotypic means to account for the varying number of litter records per sow. This ensured that means based on more observations were treated as more precise, as recommended for analyses of aggregated data (Foulley and Quaas 1995).

Results

Pedigree completeness

The results concerning pedigree completeness for both breeds are presented in Fig. 1. The analysis of the trend in the PCI-5 index for the Złotnicka White breed revealed a gradual increase in this parameter during the initial period, reflecting the formation of the breed. In 1976, the average PCI-5 level reached 0.94, followed by a sharp decline to around 0.43 in 1978. After this drop, the index began to rise again, and between 1983 and 1995, pedigree completeness across five generations remained 0.90, despite some minor fluctuations. The most significant decline in the availability of genealogical information occurred in 1998, when the average PCI-5 dropped to just 0.07. From that year on, the trend reversed again, and between 2012 and 2021, the index consistently remained above 0.90.

Fig. 1.

Fig. 1

Open in a new tab

Number of animals and their pedigree completeness index over five generations (PCI-5) obtained from the pedigrees of the Złotnicka White (A) and Złotnicka Spotted (B) populations

A similar pattern was observed for the Złotnicka Spotted breed. In this case, a steady increase in the PCI-5 was noted in the early years, associated with the gradual accumulation of pedigree information. This resulted in an average level of 0.95 being reached in 1977. In the following years, however, a noticeable decline occurred, with the average PCI-5 dropping to only 0.12 in 1981, a level it maintained for another year. The index began to rise again afterwards, although it did not reach the same level as in the Złotnicka White breed, peaking at 0.67 in 1990. In subsequent years, another sharp decrease was recorded, and by 1995, the PCI-5 level had decreased to nearly zero. From then on, the index increased steadily and has remained above 0.90 since 2008. After applying the PCI ≥ 0.9 threshold, 2,801 Złotnicka White and 1,899 Złotnicka Spotted animals were retained for further analyses.

Inbreeding level

Figure 2 presents the smoothed trend curve of the inbreeding coefficient results depending on the birth date, estimated using Wright’s or VanRaden’s method for the Złotnicka White and Złotnicka Spotted breeds.

Fig. 2.

Fig. 2

Open in a new tab

Smoothed trend of the average inbreeding coefficient by year of birth in the Złotnicka White (A) and Złotnicka Spotted (B) pig breeds, estimated using the Wright and VanRaden methods

Pedigree analysis revealed that the average inbreeding coefficient for the Złotnicka White breed, estimated using Wright’s method, was 0.0997 (max. value = 0.3831), with an average number of generations equal to 29.16. When the average inbreeding level for a given year was assigned to individuals lacking pedigree information (VanRaden’s method), the value increased to 0.2634, with a maximum level of 0.4971. For the Złotnicka Spotted breed, with an average of 21.18 generations, the average inbreeding level estimated by Wright’s method was 0.0938, with a maximum of 0.3950. Using VanRaden’s method, the average and maximum inbreeding levels were 0.2130 and 0.4988, respectively.

Analyzing Fig. 2a, a gradual divergence in the trend curves for the average inbreeding coefficient is observed, resulting from the use of different methods. Initially, both lines run parallel, with the average inbreeding level calculated using Wright’s method being noticeably lower. Between 1976 and 1981, the curve for this method shows a slight decline, after which it began to rise again in approximately 1982. The highest average inbreeding level was recorded around 1990, followed by a decline lasting approximately until 2000. In the following years, inbreeding began to increase once more. In the case of the VanRaden method, variability in the average inbreeding coefficient is also observed; however, these changes are more subtle and remain more stable over time. The trend line for this method shows a systematic increase in inbreeding levels across the analyzed period, without temporary declines observed for Wright’s method.

When comparing the average inbreeding level with pedigree completeness (PCI-5), apparent similarities can be observed, especially in the trend obtained with Wright’s method. Periods of reduced inbreeding, particularly between 1976 and 1981 and 1995–2000, coincide with a marked decline in PCI-5 values, reflecting limited genealogical information available during those years. As pedigree completeness improved after 2008, inbreeding estimates became more stable and reliable. In contrast, the effect of pedigree incompleteness was less pronounced for the VanRaden method, as its algorithm assigns average inbreeding values to individuals with missing parental information, resulting in a smoother and more consistent trend over time.

Figure 2b presents the trend curves for the Złotnicka Spotted breed. Similar to the case of the Złotnicka White breed, an initial parallel increase in the average inbreeding coefficient can be observed with both methods; however, over time, the trend lines diverge. The curve for VanRaden’s method showed an upward tendency, except from 1981 to 1990, during which a relatively stable coefficient level was observed. For the second curve, from approximately 1974, a gradual decline in the average inbreeding coefficient was observed, lasting for about 10 years. In subsequent years, the trend was characterized by slight fluctuations and remained at a similar level before beginning to rise again around 1998. In the Złotnicka Spotted breed, a relationship between PCI-5 and the inbreeding coefficient can also be observed, particularly when calculated using Wright’s method. The decrease in inbreeding between 1974 and 1982 corresponds to the decline in PCI-5 values (Fig. 1). In subsequent years, as PCI-5 increased after 2008, the growth in inbreeding became more stable and gradual. For the VanRaden method, the variability in inbreeding was smaller and the association with PCI-5 less pronounced.

Figures 3 and 4 present the estimated rates of inbreeding (ΔF) in the Złotnicka White and Złotnicka Spotted pig populations, which were calculated using the Wright and VanRaden methods over five-year intervals and expressed as percentages per year. In the most recent five-year period, the average ΔF in the Złotnicka White population was 0.87% according to Wright’s method and 0.69% according to VanRaden’s method. The values in the Złotnicka Spotted population were 1.78% (Wright) and 1.47% (VanRaden). These values represent a declining trend compared to the previous five-year period, indicating a potential slowing down of inbreeding accumulation in both breeds. Periods with lower ΔF values calculated using the Wright method overlapped with years of reduced pedigree completeness (PCI-5), as shown in Fig. 1.

Fig. 3.

Fig. 3

Open in a new tab

Rate of inbreeding (ΔF) in (A) Złotnicka White and (B) Złotnicka Spotted populations, calculated using Wright’s method over 5-year intervals, expressed as percentages

Fig. 4.

Fig. 4

Open in a new tab

Rate of inbreeding (ΔF) in (A) Złotnicka White and (B) Złotnicka Spotted populations, calculated using VanRaden’s method over 5-year intervals, expressed as percentages

An important factor affecting the future development of the population is the rate of inbreeding (ΔF), expressed as the percentage increase in the inbreeding coefficient per generation. Assuming a three-year interval between generations, the increase in inbreeding per generation was estimated. For the Złotnicka White breed, the percentages were 0.6% according to Wright’s method and 0.77% according to VanRaden’s method. These values in the Złotnicka Spotted breed population were 1.25% and 1.47%, respectively.

Effective population size

The estimates of the effective population size for pigs of the Złotnicka White and Złotnicka Spotted breeds for animals born between 2012 and 2021 are presented in Table 2. This period was selected because of the high degree of pedigree completeness, which exceeded 0.9 in both populations. For each breed, Ne was computed twice: once using Fi derived from Wright’s method and once using Fi obtained with VanRaden’s method. In both breeds, apparent differences can be observed between the results obtained using the different methods of inbreeding coefficient estimation.

Table 2.

Average effective population size of Zlotnicka White and Zlotnicka Spotted populations based on the number of animals born from 2012 to 2021, with different methods for calculating the inbreeding coefficient

Breed Złotnicka White Złotnicka Spotted
Wright’s methods 104.55 (8.36)
91.78 (0.89)
VanRaden’s methods 35.42 (1.14)
42.37 (0.19)
Open in a new tab

Inbreeding depression

The research, aimed at analyzing the impact of inbreeding, which is calculated using two different methods, on reproductive traits through linear regression models that treat inbreeding as a continuous variable, revealed no statistically significant effect of inbreeding on any of the analyzed traits. In the Złotnicka White breed (Fig. 5), the analysis of the number of piglets born alive showed a slight negative trend when inbreeding was calculated using Wright’s method, and a similarly weak positive trend when using VanRaden’s method. However, neither of these relationships was statistically significant. The analysis of the number of piglets alive at 21 days also did not show significant changes; in this case, both inbreeding coefficients indicated a weak, non-significant negative trend. Similarly, in the Złotnicka Spotted breed (Fig. 6), no statistically significant effects of inbreeding were found on either of the analyzed traits. The estimated regression coefficients indicated a weak negative trend for both traits, regardless of whether inbreeding was calculated using Wright’s or VanRaden’s method. These results suggest that in this population, an increase in inbreeding was not associated with any meaningful change in the number of piglets born alive or those surviving to 21 days of age.

Fig. 5.

Fig. 5

Open in a new tab

Effect of the inbreeding coefficient on the NBA (A, B) and NA21 (C, D) trait values estimated using linear regression models fitted in ASReml, including herd and year as fixed effects for Złotnicka White pigs. Estimated regression coefficients (β ± SE) and p-values are shown on the plots

Fig. 6.

Fig. 6

Open in a new tab

Effect of the inbreeding coefficient on the NBA (A, B) and NA21 (C, D) trait values estimated using linear regression models fitted in ASReml, including herd and year-season as fixed effects for Złotnicka Spotted pigs. Estimated regression coefficients (β ± SE) and p-values are shown on the plots

When the level of inbreeding was treated as a categorical variable, the data were divided into ten inbreeding classes, each containing approximately equal numbers of animals. Class intervals were defined as (lower, upper), meaning that the upper limit belongs to the respective class, and the classes represented increasing ranges of inbreeding values within the analyzed population.

For the ZW breed (Fig. 7), Wright’s method revealed a statistically significant effect of inbreeding group for the number of piglets born alive (NBA; p = 0.023), whereas no significant effect was observed when VanRaden’s coefficient was applied (p = 0.165). Despite the statistical significance of the model including Wright’s inbreeding coefficient, differences among classes were minor and showed no consistent increasing or decreasing pattern, with slightly higher LSMeans observed in intermediate inbreeding classes (E and D; 8.61 ± 0.43 and 8.56 ± 0.43, respectively) compared with both the lowest and highest inbreeding groups (Supplementary Tables S1–S2). For the number of piglets alive at 21 days of age (NA21), the effect of inbreeding group was significant for both Wright’s (p = 0.001) and VanRaden’s (p = 0.023) methods. However, the variation between classes was minor and did not indicate any clear linear tendency. The highest LSMeans were observed in the intermediate classes (E-F for Wright’s method and 5–6 for VanRaden’s method), while the lowest values occurred in the lowest inbreeding ranges (Supplementary Tables S3–S4; Fig. 7).

Fig. 7.

Fig. 7

Open in a new tab

Least squares means (± SE) of the analyzed traits in successive inbreeding coefficient classes calculated using Wright’s method (left column) and VanRaden’s method (right column): number of piglets born in total (NBA, top row) and number of piglets alive at 21 days of age (NA21, bottom row) in Złotnicka White pigs

When the inbreeding coefficient was treated as a categorical variable in Złotnicka Spotted pigs (Fig. 8), no statistically significant effects of inbreeding group were found for either the number of piglets born alive (NBA, p = 0.964) or the number of piglets living at 21 days (NA21, p = 0.543) when using Wright’s method. Similarly, models based on VanRaden’s method showed no significant group effects (p = 0.969 for NBA; p = 0.639 for NA21). Across both methods, mean trait values between inbreeding classes varied only slightly, showing no clear or consistent pattern. As shown in Fig. 8 and Supplementary Tables S5-S8, mean values differed only slightly between classes and did not display any systematic pattern.

Fig. 8.

Fig. 8

Open in a new tab

Least squares means (± SE) of the analyzed traits in successive inbreeding coefficient classes calculated using Wright’s method (left column) and VanRaden’s method (right column): number of piglets born in total (NBA, top row) and number of piglets alive at 21 days of age (NA21, bottom row) in Złotnicka Spotted pigs

Genetic variance components were obtained from models in which inbreeding coefficients (calculated by Wright’s or VanRaden’s methods) were included as fixed effects. Estimated variance components for NBA and NA21 were later compared with those reported by Sell-Kubiak et al. (2025). The estimates were similar, indicating that incorporating inbreeding as a fixed effect did not meaningfully affect the variance components estimation (Supplementary Table S10).

Discussion

Historic background of Złotnicka breeds

In Poland, three native pig breeds are maintained in official herd books: the Złotnicka White, Złotnicka Spotted, and Puławska breeds, all of which are included in genetic resource conservation programs (Szyndler-Nędza et al. 2014; Szulc et al. 2024). The history of Złotnicka pigs dates back to the 1950 s, when Professor Aleksandrowicz selectively bred two varieties: White, intended for meat production, and Spotted, designed for meat and fat production. Both breeds originate from primitive pigs, and the founding population consists of only five boars and eighteen sows (Ratajszczak and Buczyński 1997). In the early stages of white variety development, a process known as upgrading was applied—initially through the introduction of Swedish Landrace (Svensk Lantras) animals, and later, in 1963, to counteract the effects of selection for meat traits, Polish Large White animals were introduced (Szulc et al. 2024). Despite these efforts to increase genetic diversity in the Złotnicka White breed, the average inbreeding coefficient at that time was greater than that in the spotted variety, whose breeding relied solely on selection and mating choices (Ratajszczak and Buczyński 1997). In 1962, both varieties were officially recognized as distinct breeds, which led to the establishment of herd books. Their names derive from their origin – the Poznan University Experimental Farm, Złotniki. After 1968, when the regionalization of the Złotnicka White breed was lifted, the breed was maintained in three breeding centers (RZD Przybroda, WODR Sielinko, and PGR Michałów), although its population steadily declined. In contrast, the Złotnicka Spotted breed was maintained on two farms – Żelazno and Korsze – and a notable increase in herd numbers was observed only after 1982. The Złotnicka Spotted breed was the first to be included in a genetic resource conservation program in 1984. At that time, it was considered the only native pig breed in Poland, and the program aimed to preserve its unique genotype. The Złotnicka White breed was also included in the program a few years later. The most significant decline in the Złotnicka Spotted population occurred after 1991, due to the dissolution of state-owned farms (PGRs) and the replacement of primitive breeds with more productive meat-type breeds, resulting in the loss of several breeding lines. A particularly critical moment for the Złotnicka White breed came in 1992, when an outbreak of Swine Erysipelas occurred at the RZD Przybroda facility, significantly reducing the available breeding stock. Nevertheless, boar semen from this center was successfully preserved (Szulc et al. 2021a, b, 2025).

Since 2000, the herd books for both breeds have been maintained by the Poznań University of Life Sciences, restoring them to their place of origin. Since then, a gradual increase in population numbers has been observed in both breeds. Furthermore, the completeness of pedigree records has been steadily increasing, following earlier fluctuations that were most likely caused by historical herd relocations between breeding centers and changes in farm management. However, this recovery has been based on a minimal genetic pool, contributing to a systematic increase in inbreeding. In 2000, the Złotnicka Spotted population included only 48 sows. Despite ongoing efforts to reduce inbreeding within the framework of conservation breeding programs, studies indicate a continued increase in inbreeding levels in both breeds (Szyndler-Nedza et al., 2014), which is also confirmed by this study.

Inbreeding coefficient and effective population size

The average inbreeding level in the analyzed population (1953–2021) was 9.97% (Wright) and 26.34% (VanRaden) for the Złotnicka White breed, and 9.38% and 21.3% for the Złotnicka Spotted breed. These values are higher than those reported in previous studies (4.9% and 3.9%, respectively) (Eckert et al. 2021), which may be due to the longer time span analyzed and methodological differences. Furthermore, the annual increase in inbreeding in the Złotnicka Spotted population was markedly greater (1.47% and 1.25% according to Wright’s and VanRaden’s methods) than previously published values (0.6%). In contrast, for the Złotnicka White breed, this increase remained at a similar or slightly lower level (0.77% and 0.6% versus 0.7%) (Szyndler-Nędza et al. 2019). According to Falconer and Mackay (1996), the expected increase in inbreeding per generation should remain below 1%, highlighting the trend observed, particularly in the Złotnicka Spotted population. A comparison of the obtained results with the average inbreeding levels reported for other native pig breeds revealed that, for the Złotnicka breeds, the values calculated using both the Wright and VanRaden methods were lower than those reported for Iberian pigs (39%) (Saura et al. 2015). In relation to the Bisaro breed (10.48%) (Paixão et al. 2018) and the Korean native pig (12.5%) (Kim et al. 2019), the inbreeding coefficients calculated using Wright’s method were also lower. In contrast, the values obtained using VanRaden’s method exceeded those reported for these breeds. These differences highlight the importance of the chosen methodology when comparing inbreeding levels between populations. It should also be noted that incomplete pedigree information, including gaps present across different generations, may have affected the values of Wright’s inbreeding coefficient. Such missing records tend to underestimate inbreeding (Falconer and Mackay 1996), as unknown ancestors are treated as unrelated. The VanRaden method partially compensates for this limitation by assigning the average inbreeding value to individuals with unknown parents, thereby minimising the bias caused by missing pedigree information. Therefore, VanRaden’s approach provides more reliable estimates when pedigree information is incomplete, whereas Wright’s method is more appropriate when pedigree data are complete and well-documented (Sell-Kubiak et al. 2018).

Genomic analyses using regions of homozygosity (ROH) performed for Złotnicka pigs (Szmatoła et al. 2020) showed a substantial level of homozygosity in both breeds. Although the authors did not report a mean genomic inbreeding based on ROH for the ZW, the distribution and length of ROH segments indicate a noticeable accumulation of homozygous regions. For the ZS, the reported genomic inbreeding level (= 0.287) confirmed a high degree of homozygosity. These findings are broadly consistent with our pedigree-based estimates obtained using the VanRaden method, whereas Wright’s coefficient appears to underestimate inbreeding due to incomplete pedigree information. The results reported by Jasielczuk et al. (2020), determined based on linkage disequilibrium (LD; ZS = 23 five generations ago), were lower than the values obtained in our study using the Wright’s method. The similarity between LD-based estimates and those obtained using VanRaden’s method further indicates that approaches compensating for incomplete pedigree information may better capture the demographic signals present in the genome.

According to the widely used 50/500 rule in conservation genetics (Frankham et al. 2002), an effective population size of at least 50 individuals is required to limit short-term inbreeding, whereas a minimum of 500 individuals is needed to maintain long-term genetic diversity. Based on the estimates obtained using Wright’s method, both Złotnicka pig populations meet the minimum Ne = 50 threshold. However, when Ne was calculated using VanRaden’s method, neither population reached this recommended value. At the same time, both Złotnicka breeds were far below the Ne = 500, regardless of the estimation method used. The effective population sizes calculated using Wright’s method were higher than those previously reported by Polak et al. (2021) for Złotnicka White (Ne = 87.3) and Złotnicka Spotted (Ne = 81), whereas the values obtained with VanRaden’s method were nearly half as large. These discrepancies underscore the substantial impact of the chosen methodology on the final estimates of effective population size.

Inbreeding depression

The results obtained in our study indicate that the effect of inbreeding on the reproductive traits of Złotnicka sows was generally weak and only partially significant, with the direction and strength of this influence depending on the breed and the method used to calculate the inbreeding coefficient. In the ZW breed, a statistically significant class effect of inbreeding was detected when Wright’s method was applied (P = 0.023 for NBA and P = 0.001 for NA21), although the differences among classes were small and did not show a consistent trend. For the same breed, inbreeding coefficients calculated using the VanRaden method did not show statistically significant effects (P = 0.165 for NBA and P = 0.023 for NA21); the variation among classes was also limited. When inbreeding was treated as a continuous variable, no significant linear relationship was found for either method. Still, the trend was weakly positive, suggesting slightly higher reproductive performance at moderate levels of inbreeding. In contrast, in the ZS breed, no statistically significant effects were identified in either the Wright or VanRaden models (P > 0.5 for all traits). The overall pattern across both methods suggested a generally stable or slightly increasing trend in reproductive traits up to moderate inbreeding levels, after which reproductive performance remained relatively stable. Thus, the influence of inbreeding in both breeds appeared limited, and no consistent pattern of inbreeding depression was observed. Similar results were obtained by Szulc et al. (2006), who analyzed inbreeding depression in 143 Złotnicka White sows born between 1999 and 2004. In their study, all litters were also evaluated jointly, and the effect of inbreeding was assessed using the pedigree-based inbreeding coefficient of the sows grouped into four classes. No significant effect of inbreeding on the analyzed reproductive traits was reported, which is consistent with the results of the present study. These observations are only partly comparable to the findings of Szyndler-Nędza et al. (2014), who reported a negative effect of inbreeding on reproductive traits above a threshold of 12.5% on a small subset of data used by Sell-Kubiak et al. (2025) and in this study. It should be noted, however, that their results were based on litter inbreeding rather than dam inbreeding, which may increase the ability of such models to detect inbreeding depression. Similar patterns have been observed in other studies in which litter inbreeding had a stronger and more consistent negative effect on reproductive traits than the inbreeding level of the dam (Rodríguez et al., 1994; Tsheten and Bovenhuis 2022). In the present study, no clear decline in reproductive performance was observed even at higher levels of dam inbreeding, and the overall effect remained weak and inconsistent. However, several previous studies on commercial and other local pig breeds have demonstrated clearer effects of inbreeding depression. In Austrian Large White and Landrace pigs, a slight negative effect of inbreeding was documented (Koeck et al. 2009). Similar observations were made in Large White pigs in China, where a 10% increase in the inbreeding coefficient resulted in a decrease in NBA (Zhang et al. 2022), and in Iberian pigs, based on SNP-by-SNP analyses and genomic pedigree analysis, a similar effect of inbreeding on NBA was reported (Saura et al. 2015).

The results of this study indicate a lack of typical inbreeding depression, which may be due to the so-called purging of inbreeding depression. According to the partial dominance hypothesis, inbreeding may expose harmful recessive alleles, which are then eliminated by selection. As emphasized by Kristensen and Sørensen (2005), this phenomenon may be effective, particularly in closed populations, where selection pressure outweighs genetic drift and the eliminated alleles have a strong negative effect on traits. In the future, it would also be worthwhile to consider analysing ROH on a large scale in the Złotnicka pigs. This could provide a more accurate reflection of the impact of homozygous regions on the phenotype of interest.

Future challenges for Złotnicka pigs

To encourage breeders to maintain individuals of these breeds, subsidies for keeping boars were introduced in 2023 - previously, such support was available only for sows. Moreover, the subsidy amount was increased to 1335 PLN per pig, which is the largest in Europe for native pig breeds. This benefit aims to improve the economic viability of keeping male breeding animals and to help protect the genetic pool, thereby slowing the rate of inbreeding. However, the effects of this intervention become apparent only over time and not without additional obstacles. Since August 2023, the nucleus farm of the Złotnicka breed in Złotniki has been in a red African swine fever (ASF) zone due to an outbreak in the region. Although the herd itself remains uninfected, restrictions linked to this status have severely limited the sale of breeding males to other parts of Poland. Consequently, these limitations may reduce the effectiveness of the subsidies, potentially hindering efforts to enhance genetic diversity and control inbreeding growth.

Conslusions

Inbreeding levels continue to rise in both Złotnicka breeds, a trend expected in closed populations despite the implementation of conservation measures. In the Złotnicka Spotted breed, the rate of inbreeding per generation exceeds 1%, indicating a relatively rapid accumulation of homozygosity and a corresponding loss of genetic diversity. Although no clear or consistent evidence of inbreeding depression on reproductive traits was detected in the present study, this lack of detectable effects may be partly due to the limitations of pedigree-based inbreeding coefficients estimations resulting from pedigree incompleteness. The continuous increase in inbreeding levels highlights the need for ongoing monitoring and careful management of mating strategies. Future analyses using large-scale genomic information may provide a more accurate assessment of the actual impact of homozygosity on examined traits and may allow the detection of potential inbreeding depression effects that cannot be reliably identified using pedigree-based inbreeding coefficients alone. It should be emphasized that the inbreeding coefficient must always be interpreted in relation to the depth and completeness of the pedigree, as these factors determine the accuracy of the estimates and their biological interpretation within the studied population.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Supplementary Material 1 (DOCX 41.5 KB) (41.5KB, docx)

Author contributions

All the authors contributed to the study conception and design. Material preparation and analysis were performed by Natalia Pycińska. The first draft of the manuscript was written by Natalia Pycińska and Ewa Sell-Kubiak, and all the authors commented on previous versions. All the authors read and approved the final manuscript.

Funding

The publication was financed by the Polish Minister of Science and Higher Education as part of the Strategy of the Poznan University of Life Sciences for 2024-2026 in the field of improving scientific research and development work in priority research areas. This study was funded by a statutory fund (No.506.534.04.00) from the Faculty of Veterinary Medicine and Animal Science, Poznan University of Life Sciences, Poland.

Declarations

Ethics approval

This study uses the preexisting datasets of two Złotnicka breeds.

Consent to participate

Not applicable.

Consent to publish

Not applicable.

Competing interests

Karolina Szulc is responsible for handling Złotnicka pigs’ herd books as part of her employment at PULS. The authors have no other relevant financial or nonfinancial interests to disclose.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. Aguilar I, Misztal I (2008) Technical note: recursive algorithm for inbreeding coefficients assuming nonzero inbreeding of unknown parents. J Dairy Sci 91:1669–1672 [DOI] [PubMed] [Google Scholar]
  2. Boichard D, Maignel L, Verrier E (1997) The value of using probabilities of gene origin to measure genetic variability in a population. Genet Sel Evol 29:5–23. 10.1186/1297-9686-29-1-5 [Google Scholar]
  3. Charlesworth D, Willis JH (2009) The genetics of inbreeding depression. Nat Rev Genet 10:783–796 [DOI] [PubMed] [Google Scholar]
  4. Coster A (2022) pedigree: Pedigree functions. R package version 1.4-2. https://CRAN.R-project.org/package=pedigree
  5. de Oliveira LF, Lopes PS, Dias LCCM, e Silva LMD, Silva HT, Guimarães SEF, Marques DBD, da Silva DA, Veroneze R (2022) Estimation of genetic parameters and inbreeding depression in Piau pig breed. Trop Anim Health Prod. 10.1007/s11250-022-03428-9 [DOI] [PubMed] [Google Scholar]
  6. Eckert R, Szyndler-Nędza M, Szulc K, Skrzypczak E, Babicz M, Kropiwiec-Domańska K, Hammermeister A (2021) Analysis of genetic parameters of reproductive traits in conserved breed sows raised in Poland. Ann Anim Sci 21:843–852 [Google Scholar]
  7. Emik LO, Terrill CE (1949) Systematic procedures for calculating inbreeding coefficients. J Hered 40:51–55 [DOI] [PubMed] [Google Scholar]
  8. Falconer DS, Mackay TFC (1996) Introduction to quantitative genetics, 4th edn. Pearson Education Limited, Essex [Google Scholar]
  9. Foulley JL, Quaas RL (1995) Heterogeneous variances in Gaussian linear mixed models. Genet Sel Evol 27:211–228 [Google Scholar]
  10. Frankham R, Briscoe DA, Ballou JD (2002) Introduction to conservation genetics. Cambridge University Press, Cambridge [Google Scholar]
  11. Gilmour AR, Gogel BJ, Cullis BR, Welham S, Thompson R (2015) ASReml user guide release 4.1. VSN International Ltd., Hemel Hempstead [Google Scholar]
  12. Gutiérrez JP, Goyache F (2005) A note on ENDOG: a computer program for analysing pedigree information. J Anim Breed Genet 122:172–176 [DOI] [PubMed] [Google Scholar]
  13. Gutiérrez JP, Cervantes I, Molina A et al (2008) Individual increase in inbreeding allows estimating effective sizes from pedigrees. Genet Sel Evol 40:359. 10.1186/1297-9686-40-4-359 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Gutiérrez JP, Cervantes I, Goyache F (2009) Improving the estimation of realized effective population sizes in farm animals. J Anim Breed Genet 126:327–332. 10.1111/j.1439-0388.2009.00810.x [DOI] [PubMed] [Google Scholar]
  15. Jasielczuk I, Gurgul A, Szmatoła T, Semik-Gurgul E, Pawlina-Tyszko K, Szyndler-Nędza M, Bugno-Poniewierska M (2020) Comparison of linkage disequilibrium, effective population size and haplotype blocks in Polish Landrace and Polish native pig populations. Livest Sci 231:103887 [Google Scholar]
  16. Kim YS, Cho KH, Lee MJ, Kim JA, Cho ES, Hong JK (2019) Effects of inbreeding depression on litter size of Korean native pig. J Korea Acad Ind Coop Soc 20:514–520 [Google Scholar]
  17. Koeck A, Fuerst-Waltl B, Baumung R (2009) Effects of inbreeding on number of piglets born total, born alive and weaned in Austrian Large White and Landrace pigs. Arch Anim Breed 52:51–64 [Google Scholar]
  18. Koenig S, Simianer H (2006) Approaches to the management of inbreeding and relationship in the German Holstein dairy cattle population. Livest Sci 103:40–53 [Google Scholar]
  19. Kristensen TN, Sørensen AC (2005) Inbreeding – lessons from animal breeding, evolutionary biology and conservation genetics. Anim Sci 80:121–133 [Google Scholar]
  20. Lush JL (1945) Animal breeding plans, 3rd edn. Iowa State University Press, Ames [Google Scholar]
  21. MacCluer JW, Boyce AJ, Dyke B, Weitkamp LR, Pfenning DW, Parsons CJ (1983) Inbreeding and pedigree structure in Standardbred horses. J Hered 74:394–399 [DOI] [PubMed] [Google Scholar]
  22. Malécot G (1948) Mathematics of heredity. Hermann, Paris [Google Scholar]
  23. Paixão G, Esteves A, Payan-Carreira R, Carolino N (2018) Demographic structure and genetic diversity of the endangered Bísaro pig: evolution and current status. Arch Anim Breed 61:327–335 [Google Scholar]
  24. Polak G, Krupiński J, Martyniuk E, Calik J, Kawęcka A, Krawczyk J, Tomczyk-Wrona I (2021) The risk status of Polish local breeds under conservation programmes – new approach. Ann Anim Sci 21:125–140 [Google Scholar]
  25. Ratajszczak M, Buczyński JT (1997) Origins and development of the Polish indigenous Zlotnicka Spotted pig. Anim Sci Pap Rep 15:137–148 [Google Scholar]
  26. Rodríguez C, Rodriganez J, Silió L (1994) Genetic analysis of maternal ability in Iberian pigs. Journal of animal breeding and genetics 111(1‐6):220-227 [DOI] [PubMed]
  27. Saura M, Fernández A, Varona L, Fernández AI, de Cara MAR, Barragán C, Villanueva B (2015) Detecting inbreeding depression for reproductive traits in Iberian pigs using genome-wide data. Genet Sel Evol 47:1–9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Sell-Kubiak E, Czarniecki Ł, Strabel T (2018) Challenges in inbreeding estimation of large populations based on Polish Holstein-Friesian cattle pedigree. J Appl Genet 59:313–323 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Sell-Kubiak E, Pycińska N, Ludwiczak A, Szulc K (2025) Genetic parameters for the mean and phenotypic variability of litter size traits in native pig breeds: Złotnicka White and Złotnicka Spotted. animal 19:101602. 10.1016/j.animal.2025.101602 [DOI] [PubMed] [Google Scholar]
  30. Silió L, Barragán C, Fernández AI, García-Casco J, Rodríguez MC (2016) Assessing effective population size, coancestry and inbreeding effects on litter size using pedigree and SNP data in closed lines of the Iberian pig breed. J Anim Breed Genet 133:145–154 [DOI] [PubMed] [Google Scholar]
  31. Szmatoła T, Jasielczuk I, Semik-Gurgul E, Szyndler-Nędza M, Blicharski T, Szulc K, Gurgul A (2020) Detection of runs of homozygosity in conserved and commercial pig breeds in Poland. J Anim Breed Genet 137:571–580 [DOI] [PubMed] [Google Scholar]
  32. Szulc K, Buczyński JT, Skrzypczak E, Panek A (2006) Effect of inbreeding level on breeding performance in Zlotnicka White sows. Ann Anim Sci Suppl 2/1:61–64 [Google Scholar]
  33. Szulc K, Szyndler-Nędza M, Skrzypczak E, Luciński P (2021a) Program ochrony zasobów genetycznych świń rasy złotnickiej białej – uaktualnienie. Institute of Animal Breeding, National Research Institute, Kraków [Google Scholar]
  34. Szulc K, Szyndler-Nędza M, Skrzypczak E, Luciński P (2021b) Program ochrony zasobów genetycznych świń rasy złotnickiej pstrej – uaktualnienie. Institute of Animal Breeding, National Research Institute, Kraków [Google Scholar]
  35. Szulc K, Nowaczewski S, Skrzypczak E, Szyndler-Nędza M, Babicz M (2024) Quality and processability of meat in Polish native pigs – a review. Ann Anim Sci 24:1107–1122. 10.2478/aoas-2024-0027 [Google Scholar]
  36. Szulc K, Szyndler-Nędza M, Tyra M, Lisiak D, Kurtenkov A, Nowicki J, Nowaczewski S (2025) Effect of boar line on fattening performance and carcass and meat quality of Zlotnicka White pigs. J Anim Feed Sci 34:603–612. 10.22358/jafs/204376/2025 [Google Scholar]
  37. Szyndler-Nedza M, Mucha A, Rozycki M, Cieminski L, Blicharski T, Babicz M, Lucinski P (2014) Wpływ poziomu zinbredowania na wyniki odchowu prosiąt w obrębie ras objętych programem ochrony. Rocz Nauk Pol Tow Zootech 10:3–10 [Google Scholar]
  38. Szyndler-Nędza M, Eckert R, Szulc K, Blicharski T, Ciemiński Ł, Bartocha K (2013) Analysis of changes in the inbreeding coefficient of the Polish pig population. Rocz Nauk Pol Tow Zootech 10:3–12 [Google Scholar]
  39. Szyndler-Nędza M, Eckert R, Tyra M, Żak G, Szulc K, Blicharski T (2019) An Alysis of genetic pArAmeters of cArcAss trAits And dAily gAin of nAtive breed pigs rAised in polAnd. Annals of Animal Science 19(3):595-604. 10.2478/aoas-2019-0018
  40. Tsheten G, Bovenhuis H (2022) Inbreeding effects on reproductive traits of pureline colored pig breeds in government pig farm in Bhutan. Bhutan J Anim Sci 6:12–21 [Google Scholar]
  41. VanRaden PM (1992) Accounting for inbreeding and crossbreeding in genetic evaluation of large populations. J Dairy Sci 75:3136–3144 [Google Scholar]
  42. Wright S (1922) Coefficients of inbreeding and relationship. Am Nat 56:330–338 [Google Scholar]
  43. Zhang Y, Zhuo Y, Ning C, Zhou L, Liu JF (2022) Estimate of inbreeding depression on growth and reproductive traits in a Large White pig population. G3 Genes Genomes Genet 12:jkac118. 10.1093/g3journal/jkac118 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1 (DOCX 41.5 KB) (41.5KB, docx)

Articles from Journal of Applied Genetics are provided here courtesy of Springer

RESOURCES