A Comprehensive Review: Molecular and Genealogical Methods for Preserving the Genetic Diversity of Pigs

Abstract

Anthropogenic activities and rapidly increasing climate change have led to a significant loss of genetic diversity in domestic animals. Genealogical data have traditionally been used to monitor genetic diversity. However, due to dependency on pedigree completeness and significant errors that can occur in genealogical records, inaccurate estimation of population parameters, such as the inbreeding coefficient or effective population size, might occur. To reduce possible errors, it is necessary to combine genealogical data with molecular data. An integrated approach using genealogical and molecular data leads to the optimization of breeding programs while controlling the inbreeding that can occur within the population of domestic animals. Molecular techniques such as single nucleotide polymorphism (SNP) genotyping, whole-genome sequencing (WGS), or genome-wide association studies (GWASs) enable a detailed understanding of breed-specific genetic profiles and their use in conservation programs. In addition, molecular methods such as structural variation (SV) analysis and pangenome and epigenomic profiling provide a more comprehensive insight into genetic diversity. The conservation of genetic diversity is of particular importance for an autochthonous domestic breed due to its resilience to unfavorable climatic conditions, its specific productive traits, and its disease resistance. A combined approach of genealogical and molecular data helps to maintain genetic diversity and sustainable agricultural systems under evolving environmental challenges.

1. Genetic Diversity in Pigs

1.1. Insights from Evolution, Selection, and Conservation

From a global perspective, pigs are one of the most important livestock species. This refers in particular to their role in the food sector and to the aspect of agricultural sustainability. Their adaptability to different environmental conditions and resistance to disease are important from production and conservation perspectives [1,2]. The domestication of pigs began around 9000 to 10,000 years ago in Anatolia and China [3] and was under natural and human-mediated selection. Analyzing the pig genome provided new insights into the domestication process and evolutionary history of pigs, and highlighted the importance of maintaining genetic diversity to ensure adaptability to new production systems and current environmental changes [4,5]. This was confirmed by Bovo et al. [6], who analyzed European autochthonous pig breeds and commercial pig breeds and identified signatures of selection for adaptation to local environmental conditions and traditional breeding practices. Genetic diversity is defined as the variation of genetic characteristics within and between the populations. It is the fundamental source of biodiversity and reflects the presence of different alleles in the gene pool. It is particularly important for domestic animal populations, as they can adapt to today’s climatic challenges that are present in the world today [7] and also support sustainable production systems.

Several studies have reported higher genetic diversity in autochthonous pig populations compared to commercial breeds [8,9,10]. Muñoz et al. [8] analyzed genetic differences of European autochthonous pig breeds and found that 25% of genetic differences are due to breed differences (Fixation Index (FST) 0.25), while the remaining 75% are due to individual variation within the breeds. Diao et al. [9] also analyzed the genetic diversity of ten autochthonous pig breeds: Western commercial pig breeds, the European wild pig, Chinese autochthonous pigs originating from Guangdong and Guangxi provinces, and the Asian wild pig. The authors found that the genetic diversity of Western commercial pigs is comparable to that of Chinese pigs despite intensive selection. This contrasts with the results of [11] and Wang et al. [12], who analyzed Chinese pig breeds and found high levels of genetic diversity of autochthonous pig breeds compared to commercial breeds. Systematic processes such as migration, mutation, and selection can lead to a reduction or expansion in genetic diversity within the species [13]. Nowadays, the pig industry mainly relies on the use of cosmopolitan breeds and lines. However, the Food and Agriculture Organization (FAO) [14] reports the existence of 107 extinct and 602 non-extinct pig breeds, of which 90% are autochthonous breeds. Autochthonous pig breeds play a crucial role in maintaining genetic diversity as they are considered a genetic pool [15] for genes that have a role in disease resistance [16], meat quality traits, or production traits that are not present in commercial pig breeds [17,18]. Poklukar et al. [19] stated that interest in autochthonous pig breeds has recently increased due to the fact that society has become aware of the need to preserve the phenotypic and genetic biodiversity of autochthonous breeds. Intensive production and consumer demand could reverse this trend, favoring commercial breeds over indigenous ones. This may lead to a loss of the genetic diversity within pig breeds and necessitates the establishment of breeding programs and conservation strategies to protect existing genetic resources [20]. Eusebi et al. [21] stated that intense selection and reduced numbers of animals in populations are the leading reasons for losses of the livestock genetic biodiversity. The authors argue that combining the approach of genealogical data and molecular data provides new opportunities to estimate genetic diversity and improve selection within the population of domestic animals.

1.2. Current Challenges in Maintaining Genetic Diversity

There are several challenges that may threaten the maintenance of genetic diversity in pig populations. The loss of biodiversity within the populations is not only an environmental problem, but is also a cultural, economic, and social issue [22]. The dominance of intensive breeding practices also poses new challenges for the conservation of genetic diversity. Selection methods focusing on desirable traits lead to a reduction in genetic diversity and an increase in inbreeding [23,24]. The consequence of this reduction in genetic variability may lead to an increase in the number of deleterious variants associated with selected traits and a decrease in the ability to adapt to environmental conditions. Consumer demand for high quality pork products leads to the intensification of pig production and the use of commercial breeds, resulting in the erosion of local genetic resources and the loss of some important traits [5,24]. In addition, the genetic introgression of commercial breeds into the autochthonous breeds leads to dilution of the unique genetic characteristics of autochthonous breeds. Yang et al. [25] investigated the genetic introgression of commercial European pigs into the autochthonous Chinese breed. The authors found evidence of significant introgression levels and phenotypic changes in the economic traits of the Chinese breeds. Autochthonous pig breeds are important reservoirs of genetic diversity and play a critical role in maintaining genetic diversity within pig populations. They are reared in specific environments that have shaped and adapted them to specific environmental conditions [26,27].

The increase in the number of endangered autochthonous pig breeds and the high rate of inbreeding and genetic drift within the breeds are challenges for the conservation of genetic diversity within populations. Although 90% of global pig breeds are autochthonous, many of them are threatened with extinction [14]. This affects not only the potential loss of biodiversity, but also the ability to maintain and improve adaptive potential in populations and disease resistance [24]. A high rate of inbreeding within a small population has negative effects through inbreeding depression, which occurs as a result of mutations in the homozygous state. The occurrence of genetic drift in small populations leads to the loss of rare alleles and reduces overall genetic diversity [13,28]. A further challenge for the conservation of genetic diversity arises from consumer demands and market pressure that prioritize the use of commercial pig breeds whose products are characterized by a lower fat content [29]. In recent years, consumers have become aware of the importance of consuming high-quality and safe food that not only meets nutritional standards but also aligns with the aspect of sustainability [30]. The impact of climate changes on the conservation of genetic diversity in pig populations is reflected in increased selection pressure due to extreme conditions, the spread of disease, and habitat degradation that affects small and isolated populations [28]. The current climatic changes are reducing genetic diversity by reducing the number of individuals in populations that are less well adapted to the new conditions, thereby reducing the resilience of populations to future challenges [31,32]. Also, the influence of consumer preferences and market demands is noticeable on the erosion of genetic diversity in pig populations. Increasing demands for high-quality pork products led to the production of fast-growing pig breeds, such as Landrace or Yorkshire breeds, which resulted in a decreased number of autochthonous pig breeds and reduced genetic variation [33]. Moreover, consumer attitudes towards specific meat qualities, such as color and fat content, further exacerbate this loss of diversity. Consumer-driven pressures in favoring leaner meat have compromised programs for breeding autochthonous pig breeds [34]. Autochthonous pig breeds, which have unique genes for stress and disease resistance, need to be conserved as they are able to adapt to the changing climate conditions. To overcome these challenges, breeding programs need to be developed that integrate genetic diversity and ensure the long-term sustainability of pig populations under increasing climatic changes [35,36]

2. Pedigree Methods

Pedigree analysis has long been used as a cornerstone for the evaluation of genetic diversity, particularly in traditional breeding programs. Breeding organizations and herd books were established to document ancestry and ensure standards for different animal species. The first herd books for pigs were established in the late 1800s, including those for Berkshire and Yorkshire breeds [37], in the United Kingdom. After the establishment of herd books, pedigree-based selection became a formalized process, particularly in Europe and North America. This was largely due to the seminal work of Fisher [38] and Wright [39], which made a decisive contribution to the development of population genetics and opened numerous possibilities for the introduction of genealogical analysis in many scientific fields, including animal breeding. The most important findings from the theoretical work triggered the development of methods for estimating the genetic diversity of populations of wild and domestic animals. The development of quantitative genetics was a solid foundation for the establishment of modern breeding programs in livestock.

While in modern, economically oriented pig breeding programs the main breeding objectives are based on achieving genetic gain in economically important traits, the primary concern for traditional local pig breeds is the preservation of genetic diversity. As high genetic gain contrasts with the maintenance of genetic diversity, the balance between these objectives remains one of the greatest challenges in animal science. The loss of genetic diversity leads to the loss of alleles in the population, resulting in inbreeding depression. The first scientific findings on inbreeding depression, which refers to the decline in fitness traits in inbred individuals, were presented over a century ago by Charles Darwin [40]. In pigs, the first comprehensive analysis of the effects of inbreeding based on pedigree information was presented by Bereskin et al. [41], where the authors tested various multiple regression models to investigate the regression of litter traits in pigs on differences in inbreeding and the age of the dam. With the development of molecular techniques, the estimation of the inbreeding effect on economically important pig traits became more reliable [42,43].

2.1. Applications in Conservation of Pig Breeds

Parameters that can be used to describe genetic diversity from the pedigree include several key measures that describe the relatedness of animals in the population and the possible consequences of their mating, such as inbreeding coefficients (F), effective population size (Ne) derived from the increase in inbreeding [44], and the genetic contributions of individual ancestors. Therefore, pedigree information can be useful in estimating the effective population size, which is a critical parameter for managing population sustainability. In addition, an analysis of the genetic contributions of the founders helps maintain the genetic diversity derived from the original animals.

There are two different production concepts for pigs. Global pig production is intensive and industrialized, and is based on strict line selection within only about ten pig breeds. On the other hand, in many countries, there is a concept based on rearing pigs under extensive conditions, in which autochthonous pig breeds can play an important role. Depending on the system, breeding objective scan be focused on strong genetic improvements or conservation of genetic diversity. In both selection and conservation, some simple demographic parameters obtained from pedigrees have a major impact on the evolution of the genetic variability and depend largely on the management of the population [45,46]. Wright [47] developed the inbreeding coefficient to monitor the degree of inbreeding levels in a population. Although it is generally assumed that the loss of genetic diversity is predominantly associated with smaller, autochthonous pig populations, Welsh et al. [48] have shown using pedigree analysis that even global breeds, such as Landrace, Yorkshire, Berkshire, Duroc, and Hampshire, are also exposed to the contraction of genetic diversity. In such populations under selective pressure, inbreeding within the progeny of reproducing individuals can be higher than expected from pure genetic drift. One of the main reasons for this is the fact that selection using Best Linear Unbiased Prediction (BLUP) and genomic selection is based on pedigree information, which leads to related animals being selected together as parents of the next generation. Melka and Schenkel [49] analyzed the pedigree data of four Canadian commercial breeds and found that the Hampshire and Lacombe breeds have lost considerable genetic diversity, which needs to be conserved as a priority. Therefore, for global commercial breeds, where intensive selection is applied, pedigree analysis is used to prevent excessive narrowing of the genetic pool. Moreover, in global breeds, pedigree data have been extensively used to optimize genetic gain while controlling the risks associated with reduced genetic variability. Genetic diversity in autochthonous pigs has been the subject of numerous studies in different breeds, such as three strains of Mangalitza, Nero di Parma [50], Mora Romagnola, and Cinta Senese [51]. In most studies, the effective population size estimated from pedigrees in autochthonous pig populations indicates low genetic diversity and the need for conservation measures. Small effective population sizes increase the risk of genetic drift and loss of allelic diversity, which affects the long-term viability of the population. Additionally, the results show great variability in pedigree completeness between breeds, where some populations pedigrees are well documented and show high completeness, while in others, the values for equivalent generations are extremely low. Maintaining the genetic diversity of autochthonous pig breeds is crucial for their long-term sustainability and adaptability to changing environmental conditions. Conservation strategies should prioritize not only the preservation of genetic diversity but also maintain the cultural and economic values of these breeds. Pedigree analysis plays a crucial role in the development of effective conservation programs, as it provides data-driven insights into population structure, inbreeding levels, and genetic variability.

Inbreeding is a critical issue in the conservation and management of pig genetic resources, especially in autochthonous or closed populations with small effective population sizes. The accumulation of homozygosity due to mating between related individuals can lead to inbreeding depression, which reduces reproductive fitness, growth performance, and overall viability. The inbreeding depression load, defined as the cumulative effect of deleterious alleles exposed through inbreeding, can be estimated using pedigree-based methods [52]. Casellas et al. [53] developed a methodology based on a mixed model approach to predict individual-specific hidden inbreeding depression load, and showed on two strains of Iberian pig that including the effect of inbreeding depression load in the model was justified by its significant effect on the litter size. The method proposed a methodology having the ability to predict inbreeding load for each individual in the pedigree. The study provided evidence of a relevant genetic background with potential consequences for the reproductive performance of Iberian sows.

2.2. Applications in Selection

Currently, the management of autochthonous pig breeds is mostly focused on the conservation of genetic diversity, while genetic evaluation for economically important traits is rarely carried out, with a few exceptions such as the Iberian pig breed [54]. In autochthonous breeds, there are few studies of application of optimal contribution selection (OCS), a breeding strategy designed to maximize genetic gain while simultaneously controlling the rate of inbreeding. This is achieved by optimizing the selection and mating of individuals based on their genetic performance and their relatedness to others in the population. One of the recent studies was conducted by Škorput et al. [55], in which the authors used pedigree data to apply OCS to the Black Slavonian pig, a Croatian autochthonous pig breed. The study showed that it is possible to obtain genetic gain and maintain the genetic diversity of the analyzed population. However, the study emphasized the need to keep consistent pedigree records to obtain accurate estimates of relationships, which are the basis for creating mating plans. Pedigree information was used in combination with molecular information by Zhao et al. [1] to develop different mating strategies for small pig conservation populations. The OCS based on pedigree (POCS) was successful in reducing the inbreeding rate when truncation election was applied. A similar effect of using pedigree in controlling inbreeding in optimum contribution selection was found by Henryon et al. [56], where POCS achieved higher true genetic gain than OCS based on genomic information because it managed expected genetic drift without restricting selection at Quantitative Trait Loci (QTL). Howard et al. [35] analyzed the pedigrees of commercial pig populations with the aim of assessing the source of the selective advantage provided by OCS and concluded that the source of selective advantage from OCS comes from Mendelian sampling terms. However, practical problems arising from the low pedigree completeness and data accuracy had to be overcome by incorporating criteria for selecting candidates with sufficient genealogical information, as the optimization process is highly dependent on the quality of pedigrees [57]. Therefore, the role of genealogical information in a strategy to maintain genetic variability in populations with low production levels remains crucial, as it allows for accurate estimation of relatedness between selection candidates and inbreeding coefficients of individuals. By using pedigree data, breeders can implement optimal contribution selection effectively, ensuring that the selection of breeding animals maximizes genetic gain while minimizing inbreeding. This approach supports the long-term sustainability and adaptability of autochthonous pig breeds and preserves their unique genetic resources and cultural value.

2.3. Strengths of Pedigree Analysis

Simplicity is one of the main advantages of using genealogical information as a source of information. Pedigree analysis of genetic diversity does not require advanced molecular tools, making it cost-effective. Moreover, even average computer systems are sufficiently efficient for obtaining diversity parameters from genealogical information. Pedigree data, once established, are less expensive to maintain and analyze compared to molecular methods, which require continuous investment in genotyping [58]. If complete, genealogical information can provide a clear historical context and genetic trends in the analyzed population [59], while molecular markers capture genetic diversity at a specific time point and may not fully reflect long-term genetic changes. Pedigree data are fundamental for the development of optimal mating strategies to control inbreeding and manage genetic diversity in conservation breeding programs [60]. Therefore, molecular data are valuable but may not replace the role of pedigree records in structured breeding programs. In pig populations, pedigree data are usually well established in global breeds, such as Large White or Landrace. Pedigree analysis allows researchers to trace genealogical relationships between individuals, providing a detailed map of ancestry and lineage. This is particularly useful for understanding breed-specific dynamics, such as population bottlenecks, which occur when a breed experiences a significant reduction in its population size, leading to a decrease in genetic diversity. By analyzing pedigree records, researchers can identify historical events where the effective population size dropped, revealing potential bottlenecks. This helps to understand how certain alleles became frequent due to limited genetic diversity during that period.

2.4. Limitations of Pedigree Analysis

Data dependency is one of the greatest weaknesses of genealogical analysis. The analysis requires comprehensive and accurate pedigree records, which are often not maintained, especially when analyzing the genetic diversity of autochthonous pig breeds [15,50,61]. Low pedigree completeness was reported in several studies analyzing the genetic diversity of autochthonous pig breeds. Posta et al. [62] reported the pedigree of three strains of Mangalitza expressed as the complete generation equivalent with values of 6.01, 5.02, and 3.51. Crovetti et al. [51] reported that the complete generation equivalent in the Mora Romagnola and Cinta Senese breeds was 7.83 and 5.98, respectively. Similar results were obtained by Škorput et al. [63], who found even lower values for the autochthonous Banija spotted pig, where the number of equivalent generations was 2. Missing or incomplete records can lead to biased estimates of diversity parameters. If pedigree completeness is low, there is a lack of information about earlier generations and genetic links within population. This can lead to a high risk of overestimating diversity by underestimating relatedness in the population and consequently overestimating effective population size. If pedigree records are incomplete, the actual genetic diversity may be lower than estimated. Another weakness of using only genealogical information to estimate genetic diversity is its limited range. The main problem is the focus on genealogical relationships without taking into account variations at the molecular level (e.g., single nucleotide polymorphisms (SNP), structural variants) in the genome. In addition, pedigree information alone cannot detect de novo mutations or epigenetic factors.

3. Molecular Methods

The first genetic data were collected in the 1970s in the form of isoenzymes and alloenzymes, which were important because of the possible correlation between polymorphic alleles and economically important traits. In the 1990s, the development of DNA polymorphism screening techniques led to the replacement of protein polymorphism by DNA polymorphisms. The use of microsatellite markers has been very successful in studies to characterize the genetic diversity of breeds, to identify individuals [64,65], and in parentage testing [65]. In the 2000s, next-generation sequencing was developed on a large scale to assess genome-wide variation and is still used today [66,67]. Crow and Kimura [68] used population size and diversity of genetic markers to predict their relationship, laying the foundation for conservation genetics. The importance of preserving and maintaining the genetic diversity of pigs is demonstrated by their adaptability and productivity. This is particularly pronounced in autochthonous pig breeds, whose numbers have been declining over the last decade.

Traditional methods such as phenotypic evaluations and genealogical analyses are conventional approaches used to assess genetic diversity. However, they provide only limited insight into genetic variation within the population. With the development of molecular methods, conservation of genetic diversity has improved significantly. Yaro et al. [69,70] discussed the importance of different molecular identification methods for the conservation of domestic animals. Their review highlights the importance of restriction fragment length polymorphism (RFLP), mitochondrial DNA (mtDNA) barcoding, microsatellite markers, random amplified polymorphic DNA (RAPD), the amplified fragment length polymorphism technique (AFLP), and SNP in monitoring genetic diversity and assessing the level of inbreeding of endangered breeds. Genetic markers such as microsatellites and SNPs provide insights into genetic diversity within populations. These data can be expressed as allele frequencies or summarized at individual, population, lineage, or species levels [70]. The development of molecular methods has enabled the overcoming of significant limitations of previous approaches, such as pedigree analysis. The estimation of population parameters using pedigree analysis assumes that the base animals are unrelated. Unfortunately, this assumption is rarely met, leading to biased population parameter estimates. The use of genetic markers for assessing genetic diversity parameters is not dependent on the same assumption, and for that reason estimates of diversity parameters can be considered more reliable [71]. For this reason, Krupa et al. [61] point out that the results of the SNP data analysis should be considered for decision-making in animal conservation programs. As stated before, the reliability of pedigree information is highly dependent on the amount of information, such as pedigree depth. By using molecular approaches, this problem is efficiently overcome. While pedigree-based inbreeding estimates are indirect measures that can be inaccurate if pedigree information is incomplete or erroneous, molecular methods like genomic inbreeding coefficients (FROH, FGRM) directly measure the presence of runs of homozygosity (ROH), providing a more accurate estimate of inbreeding, even in the presence of incomplete pedigree records. Similarly, while the estimate of effective population size from genealogical information is highly dependent on pedigree depth, molecular information successfully overcomes this issue by using information of linkage disequilibrium and providing recent trends on effective population size.

3.1. Genetic Markers for Assessing Genetic Variation

The first use of microsatellite markers as a tool for assessing the genetic diversity of domestic animals began in the early 1990s. Microsatellite markers are characterized by their short length, high polymorphism, and elevated mutation rates. They are a co-dominantly inherited simple sequence repeat (SSR) that is widely distributed in a genome [72]. They have been widely employed to analyze the genetic diversity of native pig breeds and to develop region-specific breeding strategies [15,27,65,73,74,75], as well as to study their phylogenetic relationships [73,76] (

Table 1. Molecular markers used in genetic diversity studies of pig breeds.

Molecular Marker	Year	Pig Breed	Reference
Microsatellite	1994	Sus scrofa	[77]
Microsatellite	1995	Landrace, Negative, Piétrain, Large White	[78]
Microsatellite	2000	European pig breeds	[79]
Microsatellite	2008	European and Chinese pig breeds	[80]
Microsatellite	2009	Brazilian pig breeds	[81]
Microsatellite	2010	Chinese autochthonous pig breed	[82]
Microsatellite	2015	Greek black pig breed	[76]
Microsatellite	2017	Ghanaian pig breed	[83]
Microsatellite	2019	Black Slavonian pig breed	[27]
Single Nucleotide Polymorphisms (SNP)	2009	Landrace	[84]
Single Nucleotide Polymorphisms (SNP)	2013	Chinese autochthonous breeds, Asian wild boar	[85]
Single Nucleotide Polymorphisms (SNP)	2015	Duroc, Landrace, Yorkshire	[86]
Single Nucleotide Polymorphisms (SNP)	2019	European autochthonous pig breeds	[87]
Single Nucleotide Polymorphisms (SNP)	2019	Chinese autochthonous pig breeds	[9]
Single Nucleotide Polymorphisms (SNP)	2024	Korean Duroc, Landrace, Yorkshire	[88]

).

Charoensook et al. [73] and Chaweewan et al. [89] used microsatellite markers to analyze the genetic diversity of autochthonous Thai pig populations from different geographical regions and found a high degree of genetic variability within these populations. Both studies identified genetic differentiation among populations, suggesting the role of geographical isolation in their genetic structure. In addition, Charoensook et al. [73] identified private microsatellite alleles that should be conserved in the Thai pig population. Chaweewan et al. [86] also emphasized the importance of identifying different genetic clusters within indigenous Thai pig populations for conservation. Similarly, Van Ba et al. [74] used a panel of 19 microsatellite markers to characterize the genetic diversity, genetic clusters, and phylogenetic relationships of 15 autochthonous Vietnamese pig breeds, and proposed different conservation strategies for each breed based on the structure of the subpopulations. In the study by Zorc et al. [15], the authors used different marker systems, microsatellites, and SNP to analyze the genetic structure of six autochthonous pig breeds originating from three countries, i.e., Croatia, Serbia, and Slovenia. The results of their analysis show that historical and geographical factors have influenced the genetic structure of the analyzed pig breeds. The authors emphasized the need to develop conservation strategies for the preservation of genetic diversity within these autochthonous populations. Sahu et al. [75] analyzed microsatellite markers and mitochondrial DNA of autochthonous pig populations in the Himalayan region of India. Their results showed genetic admixture between the analyzed pig populations leading to increased genetic diversity.

In the genome, SNPs represent the most common form of genetic variation. They can be directly related to the function of proteins and are found in both coding and non-coding sections of genes. Due to their widespread distribution throughout the genome, they are the most commonly used genetic markers when analyzing genetic diversity. They are used for studies of evolutionary history [90], genetic structure [87,91], and the degree of admixture between autochthonous and commercial pig populations [92]. SNP markers with different densities could be used for this purpose [87,93]. Muñoz et al. [87] used a PorcineSNP60 chip to obtain information on the characterization of the genomic diversity of twenty autochthonous European pig breeds. The results showed that Turopolje, Apulo Calabrese, Casertana, Mora Romagnola, and Lithuanian pig breeds have low heterozygosity and a very small effective population size, indicating low genetic diversity in these populations. Genetic proximity was also observed with Spanish wild boar, indicating recurrent admixture between wild and domesticated pig breeds. The authors conclude that the information obtained through SNP markers provides useful information for future conservation measures, associations, or selection approaches. Similarly, Hayah et al. [90] used the Illumina PorcineSNP60 BeadChip to analyze the genetic diversity between the Landrace, Yorkshire, and Duroc breeds and to find informative SNPs for the development of cost-effective SNP panels that can be used in selection procedures. Their results showed significant genetic variation in the gene coding regions, with Landrace and Duroc being more genetically distinct than the Landrace and Yorkshire breeds. The authors also found 28 significant SNPs associated with different phenotypic traits in the pig breeds analyzed.

3.2. Genomic Approaches in Genetic Diversity Analysis

The development of whole-genome sequencing (WGS), genome-wide association studies (GWASs), and copy number variation (CNV) analysis have provided tools for studying the genomic architecture of autochthonous pig breeds (

Table 2. Genomic approaches in the study of genetic diversity of pig breeds.

Genomic Approaches	Year	Pig Breed	Reference
Whole-genome Sequencing (WGS)	2012	Duroc	[94]
Whole-genome sequencing (WGS)	2020	European autochthonous pig breeds	[6]
Genome-Wide Association Studies	2020	Different pig breeds (57)	[95]
Genome-Wide Association Studies	2020	Sus scrofa	[96]
Genome-Wide Association Studies	2022	Suhuai, Chinese Min Zhu, Large White	[43]
Epigenomic analysis	2021	Meishan, Enshi Black, Duroc, Large White	[97]
Next-generation sequencing	2022	Luchuan and Duroc breeds	[98]
Pangenome analysis	2023	Euroasia pig breeds	[99]
Copy Number Variations (CNVs)	2023	Chinese autochthonous pigs, Asian wild boars	[100]

). Furthermore, the application of these methods improves the maintenance and efficiency of breeding programs for autochthonous pig breeds. As the field of genomics continues to evolve, it will play an important role in shaping the future of pig breeding and production.

Whole-genome sequencing (WGS) is a comprehensive method that provides insight into functional genomic variation in pigs. Bovo et al. [6] analyzed the genome of 23 pig breeds, including wild boar, to identify signatures of selection that can explain the phenotypic diversity of the pig breeds analyzed. The authors used whole-genome sequencing data obtained through a DNA pool sequencing approach. The result of their study was the identification of selection signatures covering 502 unique genomic windows. The authors also compared the results with SNP chip data and showed that the two approaches can capture different types of information. A similar approach was used in the study by Poklukar et al. [19], who performed a meta-analysis of the genetic and phenotypic diversity of European autochthonous pig breeds. The authors combined DNA pool sequencing data from nineteen European autochthonous breeds and seven commercial pig breeds to identify selection signatures associated with potential candidate genes for adaptation to specific environmental conditions and production systems. In their study, Wu et al. [95] used a whole-genome approach in five pig populations to discover the genomic differences between autochthonous Chinese pigs and the Large White breed. The authors also identified 1289 non-synonymous SNPs for growth and feed conversion in Large White, which can be labeled as useful molecular markers. Gao et al. [101] analyzed the genomic breed composition of the autochthonous Chinese Ningxiang pig breed using genomic SNP information. For their analysis, the authors used SNPs with different densities to construct SNP panels that can be used as the most effective and economical SNP panels for the Ningxiang pig. The results of their study showed that the constructed reference panel (10K SNP panel) provides insight into the genomic composition of the Ningxiang breed with high accuracy and can be used for the development of low-cost, low-density chips. Similarly, Yuan et al. [11] evaluated the genetic diversity and population structure of the Tongcheng pig breed to develop and implement a conservation program and ensure acceptable genetic diversity to avoid inbreeding depression in the population. The authors used a whole-genome approach and analyzed 51,315 SNPs, of which 26,999 SNPs were identified in the Tongcheng pig breed.

Genome-wide association studies (GWASs) provide valuable insights into genetic diversity monitoring and selection signature identification in pig breeds, crucial for their integration into breeding programs and conservation strategies. The application of GWAS can help in the identification of breed-specific SNPs [11], the monitoring of inbreeding and genetic drift [96], and the identification of important genetic variants of pig breeds [102]. The study by Xu et al. [96] identified six biological phenotypes by breed traits and several production traits of 57 pig breeds. The GWAS approach identified 37 candidate genes in the analyzed pig breed, of which 10 were newly discovered candidate genes. The authors found that the use of GWAS allows efficient mapping of complex traits in a modest number of breeds with high density of genomic variants. Fang et al. [103] used a GWAS approach to detect and characterize the runs of homozygosity and estimate genomic inbreeding in a Chinese Laiwu pig breed. The authors used a high-throughput reduced-representation sequencing method developed for outbred populations to detect genomic regions with a high frequency of runs of homozygosity (ROH) regions in the Laiwu pig population. This approach shows that the Laiwu populations were affected by ancient inbreeding events and identified 13 ROH islands containing genes associated with disease resistance and biosynthetic processes. In the study by Hlongwane et al. [104], the Porcine SNP60K BeadChip was used for a genome-wide assessment of different breeds, including commercial, village, autochthonous, and feral pigs in South Africa. The results obtained show the peculiarities of South African pig populations compared to other global populations, and provide fundamental insights for breed characterization and the implementation of conservation measures.

The study of genetic diversity in pig breeds has been significantly advanced by the application of pangenomic and epigenomic approaches. The “pangenome” concept describes the entire collection of genes within a species, including the core genes and accessory genes that differ between populations. This approach can be used to identify genetic differences that contribute to breed-specific variations and adaptations [105]. Inheritable chemical modifications of DNA and histones, such as DNA methylation and histone modifications, are part of the epigenome and control gene expression without altering the DNA sequence. Epigenomic studies provide insight into how environmental factors influence gene activity and phenotypic diversity. The integration of these two approaches will lead to a more comprehensive understanding of the genetic and regulatory mechanisms of genetic diversity and adaptation [106]. The first published paper using the pangenome approach to analyze the pig genome was conducted by Li et al. [107]. By analyzing the genetic variation of nine pig breeds from Europe and Asia, the authors found a large number of novel SNPs and structural variants. They also found hundreds of millions of base pairs and protein-coding genes that are missing in the reference genome Sus scrofa 11.1 (GCF_000003025.6) but are associated with important economic traits. Several papers [99,108,109,110] used the pangenome approach to study genetic diversity within pig breeds. Li et al. [110] constructed the pangenome based on 32 pig breeds in Eurasia and analyzed coding sequence variations (presence/absence variations, PAVs) important for pig phenotypic diversity, and identified 3438 novel genes missing from the current reference genome and 308.3-Mb nonreference sequences. Similarly, Du et al. [109] constructed a pig pangenome and genome variation map of 599 deep-sequenced genes and identified 546,137 structural variations that affect adaptability to different environments and production systems. Their study showed also that core genes necessary for key biological functions are conserved in all breeds and that accessory genes enable the expression of certain breed-specific traits. The combination of pangenome and epigenome analysis leads to novel information about genetic diversity within and between pig breeds, but also about the factors that control gene expression and phenotype complex analyses such as epigenome profiling. It can also be used to investigate changes such as DNA methylation and histone modification, which regulate the expression of genes without altering the actual nucleotide sequence of the DNA strand. Li et al. [99] used long-read sequencing to detect hidden functional structural variants in pigs, leading to a better understanding of their local adaptation. The results of their study showed that when analyzing genetic diversity in pig populations, both genetic and epigenetic changes need to be considered to fully understand the range of phenotypic differences they exhibit. Pan et al. [111] also focused on their research on how the integration of epigenomic data systematically contributes to the understanding of gene regulation and adaptation at the evolutionary level in pigs. Furthermore, the integration of epigenomic profiles into the pangenome enables a deeper understanding of the adaptive changes of different pig breeds in response to their environment. Liu et al. [98] emphasized the need for such integration in their work on the chromatin accessibility landscape in pigs. They showed that the way epigenetic information can modify gene expression patterns is an important question lying at the nexus of genetics and environment.

4. Combined Approaches in Assessing Genetic Diversity in Pig Breeds

The integration of different techniques, such as microsatellite markers, SNP genotyping, and pedigree analysis, provides a comprehensive overview of genetic variability, population structure, and breeding strategies. Recent studies [15,59,108] have demonstrated the effectiveness of integrating these techniques to enhance the assessment of genetic diversity across various pig breeds (

Table 3. Combine approaches in the study of genetic diversity of pig breeds.

Approaches	Year	Pig Breed	Reference
Pedigree, SNP	2013	Iberian pig breed	[112]
Pedigree, SNP	2016	Landrace, Large White	[71]
Microsatellite, pedigree	2018	Banija spotted pig breed	[63]
Microsatellite, pedigree	2020	Black Slavonian pig breed	[114]
Pedigree, SNP	2021	Přeštice Black-Pied pig breed	[61]
Microsatellite, pedigree, SNP	2022	Autochthonous pig breeds (Croatia, Slovenia, Serbia)	[15]

). In the study by Zorc et al. [15], the authors used an integrated approach of microsatellite markers, SNP data, and pedigree information to analyze the genetic diversity and relationships of autochthonous pig breeds from Croatia, Slovenia, and Serbia. The authors found that although SNP panels provide a broader distribution of informativeness for assignment compared to microsatellite markers, both methods successfully distinguish distinct genetic clusters of individual breeds. Silió et al. [112], Zanella et al. [71], and Krupa et al. [61] used pedigree and SNP analysis to analyze the Iberian pig breed, Landrace and Large White breeds, and the Přeštice Black-Pied pig breed. Also, Zanella et al. [110] found that inbreeding coefficients derived from pedigree data were lower than those estimated from SNP data. A combined approach to analyzing genetic diversity is useful in populations with shallow pedigrees. Most researchers have shown that genetic diversity declines as pedigree completeness increases. This could also be attributed to the homogenization of breed characteristics and the limited number of available breeding individuals [113]. In order to obtain a reliable comparison of population parameters from different sources, it is necessary to calculate the correlations between the different results. Krupa et al. [61] reported moderate correlations between pedigree-based inbreeding (Fped) and SNP marker-based inbreeding (Froh), while other authors reported low correlations between Fped and Froh [71]. These studies, such as those based on SNP data, suggest that genomic inbreeding may provide a more accurate assessment of inbreeding levels compared to traditional pedigree-based methods, especially in breeds where pedigree recording is not precise or complete. These discrepancies highlight the importance of integrating genomic information into breeding programs to more effectively control inbreeding and preserve genetic diversity.

In future perspectives of molecular methods, an increase in the application of artificial intelligence (AI) techniques is expected. However, AI has already been present in the analysis of pig genome in various ways. One of the first applications of artificial neural networks was carried out on a European pig population [115], where the application of the method provided additional information on the within- and between-population diversity, allowed differences between similar populations to be highlighted, and helped differentiate different groups of populations. A machine learning approach using the random forest method was tested by Schiavo et al. [116] to analyze genotyping data of pigs, with the task of assigning animals to breed; this method showed advantages compared to earlier methods. In the future, AI can be used to build predictive models that forecast genetic diversity outcomes under different breeding strategies. Machine learning algorithms can analyze large datasets from genomic, pedigree, and phenotypic data to predict the impact of various selection and breeding programs on genetic variation and inbreeding levels. AI can also help in the identification and tracking inbreeding patterns using genomic data. Machine learning algorithms can detect runs of homozygosity (ROH) and predict inbreeding coefficients more accurately than traditional methods. This allows breeders to manage and mitigate the risk of inbreeding and reduce associated health problems in pig populations. Methods within the AI framework might be useful in population structure analysis. AI techniques can be applied to understand population structure by clustering pigs based on genetic data. This helps in identifying subpopulations with unique genetic characteristics, which can be crucial for conservation efforts and breed improvement programs. Optimization of breeding programs can be boosted by using AI techniques to analyze genomic and pedigree data to recommend the best mating pairs, and improve genetic diversity and trait selection, while minimizing risks like inbreeding. AI algorithms can continuously update and refine recommendations based on ongoing genetic data and breeding results.

5. Conclusions

The genetic diversity of both global and autochthonous pig breeds is under pressure, and its conservation remains one of the greatest challenges in breeding management. The assessment of genetic diversity from various sources enables effective management and mating planning with the aim of selecting unrelated or minimally related animals as parents for future generations.

Historically, genealogical information from pedigrees played a crucial role in population genetics and in the estimation of population parameters, such as the inbreeding coefficient and effective population size. With the development of molecular methods and the assessment of genetic diversity by molecular markers like microsatellites and SNP markers, the problems of unreliable parameter estimation from incomplete or inaccurate pedigrees have been overcome. Therefore, the combined application of both methods provides the most reliable estimates of population parameters, especially in those pig populations where pedigree recording is insufficient.

Future trends in the assessment of genetic diversity in pigs are likely to focus on the use of high-throughput genomic technologies such as whole-genome sequencing or genome-wide association studies. These approaches provide a more detailed understanding of genetic variation at the nucleotide level and enable the identification of genomic regions associated with important traits. In addition, the integration of genomic data with advanced computational tools, such as machine learning and artificial intelligence, is expected to increase the accuracy of diversity estimates and improve breeding strategies. This holistic approach will contribute to the sustainable management and conservation of genetic resources in the pig population.