1 Introduction

Goats play a crucial role in global agriculture and animal husbandry. They are among the earliest domesticated animals and still provide meat, milk and fiber to this day. It is particularly important for small-scale farmers and residents in remote areas (Lu, 2023). At present, there are already hundreds of varieties in the world. It is distributed from high mountains to hot deserts and has strong adaptability (Nanaei et al., 2023).

The advancement of DNA sequencing technology has enabled a clearer understanding of the evolution and traits of goats at the genomic level. Genome-wide analysis thus traced early domestication events and subsequent migration routes (Colli et al., 2018; Daly et al., 2021). Meanwhile, related studies have also compared genetic differences among different varieties and precisely located genes associated with important traits (Brito et al., 2017; Sasazaki et al., 2023). However, a long-standing limitation remains obvious: most studies rely on a single reference genome, and thus may miss some aspects of species genetic diversity (Li et al., 2023a).

The concept of "pan-genome" originated from microbiology. The core of it is to gather all the genes of a species - including both the core genes shared by all individuals and the variant genes that only occur in some individuals. In humans and crops, pan-genomics has revealed many previously overlooked gene versions (Gong et al., 2023). Take humans as an example. The latest pan-genome has added approximately 119 million DNA "building blocks" and thousands of duplicate genes, significantly enhancing the ability to detect structural variations (Liao et al., 2023). Similar situations also occur in crops such as tomatoes, among which rare alleles that affect traits such as flavor have been identified (Gao et al., 2019). Pangenomics, on the one hand, broadens the understanding of genetic diversity, and on the other hand, clarifies the sources of individual differences.

In recent years, the concept of pan-genome has begun to be applied to the research of livestock genomes and has made initial progress (Gong et al., 2023). It is of great significance to construct a pan-genome for the Capra genus, which includes both many wild relatives and domestic goats. On the one hand, the genomes of wild goat species and domesticated species can be comprehensively analyzed to reveal the phylogenetic sources and effects of genomic variations during domestication (Bao et al., 2019; Sasazaki et al., 2023; Liu et al., 2024). On the other hand, the genes and sequences specific to goat breeds in different ecological environments can be captured, which is helpful for analyzing the broad adaptability basis of goats (Li et al., 2020; Nanaei et al., 2023).

This study aims to construct and analyze the pan-genome of the genus Goats, systematically explain the roles of the core and variable genomes in the evolution, domestication and environmental adaptation of goats, review the species classification, domestication history and existing genomic research background of the genus goats, then introduce the methodological route of pan-genome construction, and further analyze the conserved function of the core genome and the adaptive characteristics of the variable genome At the same time, the application prospects and challenges faced by the pan-genome in the research of goat evolution and breeding were also discussed. This research not only provides new evidence for analyzing the past evolutionary path of goats, but also offers valuable support for future-oriented goat breeding and the conservation of endangered wild goats.

2 The Background of Classification, Domestication and Genomic Research of the Genus Goats

2.1 Diversity of wild goat species

The Capra genus encompasses a variety of wild goats and wild goats, mainly distributed in the high mountains and rugged regions of Eurasia and northeastern Africa. Many groups have long lived in isolated areas and evolved independently, thus showing obvious genetic differentiation (Nair et al., 2021). They are related to domestic goats, but there are significant differences in chromosome composition and genomic sequence (Bao et al., 2019).

In recent years, large-scale sequencing has begun to incorporate the genomes of wild goats. Take the vargoat project as an example. The whole genome data of 1 159 goats worldwide were collected, among which 35 represented 8 wild species (Denoyelle et al., 2021). These results further highlight the genetic gap between wild and domestic goats and provide key information for analyzing the infiltration of wild genes into domestic goat breeds (Bao et al., 2019).

2.2 Domestication centers and events of domestic goats

Domestic goats (Capra hircus) first came from Southwest Asia, where they were domesticated from wild Persian goats (C. aegagrus) about 8 000~10 000 BC (Zheng et al., 2020; Wang et al., 2021). Archaeology and paleogenomics suggest that goat domestication was not a single event but a “mosaic” process with several sources and stages (Daly et al., 2018). Studies of ancient genomes show that in different areas of the Fertile Crescent, such as the Zagros Mountains and Anatolian Plateau, goats were domesticated separately, and later gene flow took place between groups. At the Ganj Dareh site in Iran, mud bricks with goat hoof marks were found, showing their early presence in human settlements (Figure 1). In addition, genome sequencing of goat remains from about 10,000 years ago in the Zagros Mountains showed that these early herds were closely linked to nearby wild goats but also showed genetic gaps from goats in other regions, supporting a multi-center domestication pattern (Daly et al., 2021).

After humans began raising goats, flocks of sheep were frequently transported to brand-new territories far from their native habitats. Migration then began, with groups spreading outward and their footprints spread across many landscapes. In unfamiliar environments, domestic goats frequently encounter and crossbreed with local wild goats. Genomic evidence suggests that early hybridization events with Caucasian wild goats and falconeri (C. falconeri) did occur, thereby introducing new genetic variations into domesticated populations (Bao et al., 2019; Sasazaki et al., 2021). These ancient gene exchanges still leave traces in DNA to this day. At present, domestic goats around the world have largely merged into several major lineages. Each lineage corresponds one-to-one with specific geographical regions and also reflects the initial domestication centers (Colli et al., 2018; Bian et al., 2024).

2.3 Broad phenotypic adaptability of goats

Goats are well known for adapting to many different habitats. Over time, they were taken to all parts of the world, from cold mountains to hot deserts and even wet tropical zones, and could still live and reproduce (Nanaei et al., 2023). Local breeds developed traits suited to their environments through natural selection and human breeding. For example, goats in the Qinghai–Tibet Plateau and Himalayas show high-altitude adaptations to survive low oxygen.

Studies have shown that certain alleles of EPAS1 are positively selected in plateau goats, enhancing their blood oxygen-carrying capacity and helping goats overcome the hypoxic environment at high altitudes (Lu et al., 2025). For instance, in the arid and hot regions of the Middle East and North Africa, goat breeds have demonstrated tolerance to high-temperature and water-scarce environments. Some tropical native goats have special physiological mechanisms in body temperature regulation, metabolism and skin heat dissipation, and genes such as heat shock proteins (such as HSP70) in their genomes show selection signals (Li et al., 2020).

Recent studies have also found that goats living in desert environments such as the Arabian Peninsula have specific variations in their genomes that originated from ancient wild species, which may have been introduced through ancient hybridization and are associated with drought tolerance traits (Sasazaki et al., 2021). In alpine and cold environments, goats in regions such as Siberia and Mongolia have thick and dense coats and stronger heat production capacity, and adaptive changes have also occurred in heat-related genes such as UCP1 (Li et al., 2020).

3 The Current Status of Genomic Research on the Genus Goats

3.1 Classification and distribution of the genus goats

The genus Gobius includes domestic goats and several wild relatives. Together they form a distinct group in the subfamily Gobiinae. Genetic and evolutionary data show that the domestic goat (C. hircus) is closest to the Persian wild goat (C. aegagrus). Other wild forms-Siberian wild goat, alpine wild goat (C. ibex), Caucasian wild goat, and the Markhor (C. falconeri)-sit on separate side lineages (Bao et al., 2019). These species live mainly in the Old World’s mountain regions. Long geographic isolation has shaped clear patterns of spread and split (Nair et al., 2021).

Scientists have studied goat genes from around the world. They found that today's farm goats still carry some genes from their wild relatives. For example, some goat breeds in Europe and the Middle East have special mitochondrial types that came from Alpine or Caucasian wild goats (Bao et al., 2019). This shows that wild and domestic goats mixed long ago. Other studies looked at DNA markers from goats in Asia, Africa, and Europe. They found that goat groups are very different between regions. These studies also found signs that goats moved with ancient people when they migrated (Colli et al., 2018).

3.2 Existing reference genome resources and limitations

Research on the goat genome began with the construction of reference genomes for individual breeds. The first goat reference genome was from the Yunnan Black goat, and a genome sequence of approximately 2.6 billion bases was published in 2013 (Dong et al., 2013). Subsequently, the United States Department of Agriculture team constructed a higher-quality goat reference genome ARS1 in 2017 using advanced single-molecule sequencing and chromosome conformation capture techniques (Bickhart et al., 2017). These reference genomes provide an important foundation for the identification of functional genes, comparative genomics and breeding research in goats. However, since the reference genome only represents the genetic composition of a single individual (or a single species), it cannot encompass all the variations of the entire species (Li et al., 2023a). Studies have shown that compared with the reference sequence of goats, different breeds and wild relatives carry a large number of sequence fragments and genes "missing" from the reference genome (Pogorevc et al., 2024). Furthermore, many structural variations (such as long fragment insertions/deletions, gene copy number variations, etc.) are not easily detected in reference-based variation detection, resulting in biases in the understanding of certain functional variations (Li et al., 2019; Li et al., 2023a; Li et al., 2023b).

3.3 Progress in the application of pan-genome in livestock

Research on the pan-genome of livestock is advancing rapidly, and the picture of genetic differences within and outside species is being drawn clearer and deeper. Pigs are a typical example: there are approximately 206 million DNA base gaps in the primary reference genome, and a vast number of structural variations have been detected, among which there are many genes related to high-altitude adaptation and reproductive strategies (Li et al., 2020). The same is true for sheep - 195 million new bases and 2 678 previously unannotated genes have been added; Meanwhile, variations related to key traits such as tail shape (fat tail, thin tail) were discovered (Dai et al., 2023). The progress of cattle has gone even further. After integrating multi-variety long-read assemblies, Crysnanto et al. (2021) constructed a multi-assembly genome map and revealed a large number of new functional fragments. As a result, the complexity of the bovine genome is presented in greater detail.

For goats, early exploration has already begun: Liao et al. (2023) were the first to attempt to supplement the missing fragments in the goat reference genome by splicing the genomes of several closely related species; Subsequently, Li et al. (2023b) constructed the goat pan-genome using hundreds of global goat genomic data and achieved valuable results. It can be foreseen that the in-depth research on the pan-genome of the Goat genus will further benchmark against the research achievements of other domestic animals, thereby comprehensively enhancing our understanding of genomic variations and traits in domestic animals.

4 Methods and Technical Routes for Constructing the Pan-genome

4.1 Basic concepts and components of the pan-genome

The pan-genome is a collection of genomic sequences of all individuals within a certain species or taxonomic unit, consisting of two parts: the "core genome" and the "variable genome" (Gao et al., 2019). The core genome refers to the sequences and genes that exist in all individuals, typically including conserved functional elements necessary for maintaining basic life activities. A variable genome (also known as a supplementary genome or variable part) is composed of sequences that are not shared by all individuals, including fragments specific to a particular subgroup, species, or even an individual. In practice, the pan-genome is often represented in the form of a "non-redundant sequence set", that is, by integrating the gene assembly of multiple individuals and removing repetitive regions, the union of all unique sequences is obtained (Liao et al., 2023). The proposal of the pan-genome has greatly promoted the understanding of intra-species variation patterns, extending from microorganisms to animals and plants, providing a new perspective for the study of genomic evolution and function (Gao et al., 2019; Gong et al., 2023).

4.2 The construction process of the Goat genus pan-genome

This study adopted a systematic approach to construct the pan-genome of the genus goats. In terms of sample selection, the major domestic goat breeds worldwide (Asian, African, European native breeds and improved breeds) and wild relatives (ibex, northern goat, etc.) were covered to ensure lineage and geographical representativeness (Li et al., 2023b); Data acquisition was achieved using PacBio/Nanopore long-read sequencing to obtain chromosome-level assembly, combined with short-read resequencing data to supplement variations (Crysnanto et al., 2021). The specific process includes: identification of non-reference insertion fragments by multiple sequence alignment (Liao et al., 2023); Graph structure splicing and integration of new sequences to construct a graph pan-genome with multiple branches (Bao et al., 2019); "Map-to-pan" iterative strategy: Unaligned reads are reassembled and incorporated into the pan-genome; Generate a non-redundant sequence set and a presence/absence matrix. The entire process requires the comprehensive application of assembly and alignment tools and manual verification to ensure sequence accuracy (Crysnanto et al., 2021; Li et al., 2023b). This process can effectively capture the rich structural variations of the genus goats, providing comprehensive genomic resources for population analysis.

4.3 Data mining and functional annotation tools

This study adopted a clear process to conduct functional labeling and biological interpretation of the goat pan-genome. First, use tools such as MAKER to predict the gene model in the new sequence; Then, the annotation was completed by searching databases such as NCBI NR and UniProt with BLAST+ (Li et al., 2023b). For newly discovered variant regions, GWAS and population genetic statistics (such as F_ST) were used to detect their associations with population structure and trait selection (Sasazaki et al., 2021).

The outline of gene functions has become clear. Core genes undertake the underlying affairs of cells, such as metabolism. In contrast, variant genes are more often involved in shaping adaption-related traits, such as disease resistance (Gao et al., 2019; Li et al., 2020). To further reveal its mechanism, this study integrates multiple layers of biological data. Transcriptomics is used to track expression fluctuations and also to assess how DNA variations switch genes. Epigenomics describes the alterations in chromatin state and chromosome configuration (Denoyelle et al., 2021). This combinatorial strategy not only reveals historical selection signals, but also captures events such as gene loss and the clearance of harmful mutations during the domestication stage (Li et al., 2023b). With the iteration of computing tools, pan-genomic datasets are expected to more efficiently locate key DNA differences and further explain the genetic basis of phenotypic diversity and environmental adaptation in goats.

5 Analysis of the Functional Characteristics of the Core and Alternative Genomes

5.1 Conserved functions of core genes

The core genes in the goat pan-genome are ubiquitous in all individuals and mainly undertake the basic functions of maintaining life activities, thus being highly conserved in evolution. These genes are mostly involved in metabolism, cell structure, reproduction and development. For instance, ribosomal proteins, metabolic enzymes and cytoskeletal proteins remain almost unchanged in all goats, demonstrating their indispensability. The key genes in the signaling pathway are also highly consistent among different varieties, indicating that they are strongly functionally constrained and prevent the accumulation of harmful mutations. GO functional enrichment analysis revealed that core genes were concentrated in basic categories such as "metabolic processes", "cell cycle", and "nucleic acid synthesis" (Gao et al., 2019). Similar to other domestic animals, core genes account for the majority of the total number of genes (more than 90% in chickens (Li et al., 2020), while a few variable genes are associated with specific functions. This indicates that core genes ensure species survival by stably performing key life processes, and at the same time provides an important reference for cross-species comparative genomics.

5.2 Environmental adaptability associations of variable genomes

Goat populations display genetic differences shaped by local adaptation and by human breeding. High-elevation habitats are harsh-thin air, cold, and intense sun. In mountain goats, HSP genes buffer proteins and bolster immunity (Figure 2). They also carry distinctive variants in oxygen-sensing genes such as EPAS1 and HIF1A, boosting red-blood-cell production and oxygen transport (Lu et al., 2025).

In hot and arid regions, the loci of heat shock genes such as HSP70 often undergo changes. In cold climates, the situation is different. The variations of UCP1 and FGF5 regulate heat production and also promote wool growth. The artificially selected imprints are clear: Dairy goats are enriched with milk-related genes, while Angora goats accumulate more fiber gene loci (Li et al., 2023b). The differences in immune structures are also obvious. The TLR lineages of different groups are not consistent, reflecting the disease ecology and pathogen pressure in various regions (Li et al., 2020). The combination of the above models enables goats to resist cold and heat, tolerate hypoxia and enhance their disease resistance.

5.3 Selection signals of variable regions and population specificity

Pan-genome analysis revealed selective footprints and population-specific translocations. Some gene fragments were absent in farm goats but still visible in wild relatives (Li et al., 2023b). Such deletions mostly involve genes related to behavior or reproduction, suggesting the "pruning" of genes during the domestication process. Regional differences are equally distinct: African goats are more likely to carry antiparasitic and heat-tolerant alleles, while East Asian goats are rich in variations that determine coat color and body size (Britol et al., 2017; Bao et al., 2019; Nanaei et al., 2023). Many loci related to domestication are common in farmed populations but rare in wild populations, and this pattern conforms to the characteristics of rapid selection (Dai et al., 2023). More notably, similar changes have occurred in the growth and reproductive pathways of goats and sheep, reflecting parallel evolution under livestock pressure (Yang et al., 2024).

6 The Application of the Pan-genome in the Research of Goat Evolution and Domestication

6.1 The contribution of genomic structural changes during domestication events

Goat domestication was accompanied by significant genomic structural remodeling, and the pan-genome revealed its important role in domesticated traits (Li et al., 2023b). Domestic groups lost some genes related to sensation, stress and social interaction, reduced alertness and aggression, and showed a negative selection of wildness and reproductive cycle. Some structural variations directly shape the phenotype. For instance, a deletion of approximately 12 kb leads to a hornless trait, which, although accompanied by recessive defects, is fixed due to its advantage in breeding. Gene infiltration also provides an additional source of variation for domestication. Some body type and coat color genes may originate from hybridization with wild ibex (Dai et al., 2023). For example, the genes of the Caucasian ibex enhance cold resistance, and the genes of the Markhor sheep enhance the ability to tolerate poor soil feed (Bao et al., 2019). The pan-genome thus becomes an important tool for analyzing the genetic mechanism of the domestication process.

6.2 Reassessment of genetic diversity and breeding potential

With only a few genetic markers, the diversity of goats is often not fully observed. The introduction of the pan-genome can incorporate multiple types of DNA variations into the analysis together. Minor changes like SNPS are easier to detect, and larger structural differences are also clearer. The available marker set was expanded, and the success rate of genome selection increased accordingly (Li et al., 2023b). It is also possible to locate population-specific genes missing in the reference genome, such as genes related to disease resistance or heat tolerance in African and South Asian goats (Sasazaki et al., 2021), bringing new materials for breeding.

Pan-genomic data can more accurately measure the genetic distance and diversity between populations, thereby providing a basis for more targeted conservation and hybridization programs. The "Vargoat" project provides intuitive evidence: the genetic diversity of global goats is extremely high, and some local breeds carry unique variations that urgently need priority protection (Denoyelle et al., 2021). Furthermore, many newly identified DNA fragments are adjacent to QTLS with traits such as milk yield and meat yield (Yang et al., 2024; Azam et al., 2025), suggesting that structural variations can serve as practical markers in breeding.

6.3 Comparative insights with the pan-genome of other species

Cross-species comparisons reveal both commonalities and differences. After domestication, many domestic animals have experienced genomic "contraction" : wild populations retain more unique sequences and structural variants, while domesticated breeds are more uniform (Yang et al., 2024). This pattern supports the view that the "domestication syndrome" has led to a decline in diversity. The differences were equally striking - the main changes in sheep pointed to lipid metabolism (Dai et al., 2023); The signals of goats are more focused on behavioral and reproductive pathways (Li et al., 2023b).

Intergenus studies provide clues to speciation and adaptation. The bison pan-genome simultaneously identified unique and shared sequences pointing to a common ancestor or cross-species gene flow (Zhou et al., 2022). Extending similar work to all goat species can help clarify pedigree boundaries and highlight conserved genes and innovative genes. Methods from other fields can also be referred to: The human pan-genome uses graph structure and long-read sequencing to resolve complex regions (Liao et al., 2023), and this approach is applicable to the study of immune loci in goats (Gong et al., 2023). Studies on pigs have also shown that disease-resistant genes are often preserved in local breeds (Li et al., 2020); Goat breeding should incorporate these local superior genes into the system.

7 Research Challenges and Future Prospects

7.1 Technical and computational challenges

The application of the pan-genome in higher animals such as goats still faces technical and computational challenges. Constructing a high-quality pan-genome requires high-precision assembly of multiple individuals. However, due to the existence of repetitive sequences and complex regions, chromosome-level assembly is still not perfect, and there are often blanks in regions such as centromeres and ribosomal DNA. Future T2T assembly technology is expected to improve this situation (Gong et al., 2023). The pan-genome integrates dozens of long-read assemblies and has extremely high requirements for storage, memory and computing efficiency. The accuracy and speed of the existing Graph Genome algorithm in repetitive regions are still insufficient. Genome-wide genotype inference and association analysis require more efficient processes, and visualization and data sharing also urgently need new tool support. The integration of genomic, phenotypic and environmental data from different sources is rather difficult, and there is a lack of unified processing standards. The field of livestock has not yet formed a mature graphic genome format and database, which limits the comparison and application among studies. To unlock the potential of the pan-genome, it is necessary to improve assembly algorithms, utilize cloud computing and parallel computing to process big data, and develop specialized analysis and sharing platforms, thereby promoting its regular application in livestock genomics.

7.2 Trends in functional verification and multi-omics integration

The pan-genome has produced a large number of candidate variations, but it is still not easy to prove their true functions. It is difficult to conduct large-scale functional tests on domestic animals such as goats, but molecular-level verification is advancing. For instance, CRISPR/Cas9 has been used in hornless goats, indicating that it is feasible to conduct functional tests in livestock. Combining transcriptome, proteome and epigenome data can narrow the candidate range and enhance the strength of evidence (Li et al., 2020; Gong et al., 2023). Structural variations in non-coding regions may regulate gene activity and need to be detected by means of ATAC-seq or ChIP-seq. Population genetic analysis can also provide clues: variations enriched in extreme trait groups are often related to phenotypes. Global collaboration and resource sharing will promote the functional analysis of both encoded and non-encoded components. Subsequent research should pay more attention to the variation and evolutionary conservation of regulatory sequences, and explain the mechanism of trait changes at the gene network level.

7.3 The combination of pan-genomics and conservation genomics

The goat pan-genome is useful for breeding and also helps protect wild goat relatives. Many wild goats are endangered but still carry rare and useful genes (Bao et al., 2019). A pan-genome can identify genes that only exist in wild species. This information helps plan protection and careful breeding programs. Genes for disease resistance or environmental tolerance found in wild goats should be preserved. These genes can later be introduced into domestic goats if needed (Sasazaki et al., 2021).

The pan-genome can also measure the natural transfer amount of genes between wild goats and domestic goats. This helps managers strike a balance between retaining purebred breeds and allowing for necessary adaptations. For very small populations, discovering their unique genetic variations can help zoos and breeding programs maintain diversity and prevent gene loss (Gong et al., 2023).

8 Concluding Remarks

This research built a pan-genome of the goat genus and clearly showed the wide genetic diversity in goats and its part in evolution and adaptation. The core genome, shared by all goats, provides the basic genetic foundation and keeps the main life functions stable, staying highly conserved through long evolutionary time. The variable genome reflects how goats respond to different environments and human-driven selection. The structural changes and new genetic elements it contains help form the special traits seen in different goat breeds and their wild relatives.

The gene deletion and sequence rearrangement that occurred during the domestication of domestic goats played an important role in the formation of domesticated traits. The unique genetic variations of different ecological types of goats provide genetic support for them to cope with extreme environments such as hypoxia, extreme heat and drought at high altitudes. Pan-genome analysis also enables us to reevaluate the genetic diversity of goats, discover a large number of variations not covered by traditional reference genomes, and thus provide a more complete list of genetic resources for goat breeding and conservation. Pan-genome comparisons with species such as pigs, cattle and sheep show that domestic animal domestication not only has common patterns at the genetic level (such as contraction of genetic diversity and conservation of core functional genes), but also exhibits species-specific evolutionary innovations.

Looking forward, as sequencing technology and bioinformatics continue to improve, the pan-genome is likely to become the common approach in livestock genomics studies. For goats, building a larger and more accurate pan-genome, together with functional genomics and multi-omics integration, offers strong potential to uncover the genetic basis of complex traits and support breeding progress. At the same time, applying the pan-genome idea to conservation genomics will provide useful guidance for protecting goat genetic resources and preserving the genetic diversity of both species and breeds.

Acknowledgments

We sincerely appreciate the valuable opinions and suggestions provided by the three anonymous reviewers, whose meticulous review helped us improve the quality of this manuscript.

Conflict of Interest Disclosure

The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

References

Azam S., Sahu A., Pandey N.K., Neupane M., Van Tassell C.P., Rosen B.D., Gandham R., Rath S., and Majumdar S.S., 2025, Constructing a draft Indian cattle pangenome using short-read sequencing, Communications Biology, 8(1): 605.

https://doi.org/10.1038/s42003-025-07978-0

Bao W., Lei C., and Wen W., 2019, Genomic insights into ruminant evolution: from past to future prospects, Zoological Research, 40(6): 476.

https://doi.org/10.24272/j.issn.2095-8137.2019.061

Bian P., Li J., Zhou S., Wang X., Gong M., Guo X., Cai Y., Yang Q., Fu J., Li R., Huang S., Luo F., Shah A.M., Lenstra J.A., Mwacharo J.M., Li R., Ren G., Wang X., Li C., Zheng W., Jiang Y., and Wang X., 2024, A graph-based goat pangenome reveals structural variations involved in domestication and adaptation, Molecular Biology and Evolution, 41(12): msae251.

https://doi.org/10.1093/molbev/msae251

Bickhart D.M., Rosen B.D., Koren S., Sayre B.L., Hastie A.R., Chan S., Lee J., Lam E., Liachko I., Sullivan S., Burton J., Huson H., Nystrom J., Kelley C., Hutchison J., Zhou Y., Sun J., Crisà A., De León P., Schwartz J., Hammond J., Waldbieser G., Schroeder S., Liu G., Dunham M., Shendure J., Sonstegard T., Phillippy A., Van Tassell C., and Smith T.P., 2017, Single-molecule sequencing and chromatin conformation capture enable de novo reference assembly of the domestic goat genome, Nature Genetics, 49(4): 643-650.

https://doi.org/10.1038/ng.3802

Brito L.F., Kijas J.W., Ventura R.V., Sargolzaei M., Porto-Neto L.R., Cánovas A., Feng Z., Jafarikia M., and Schenkel F.S., 2017, Genetic diversity and signatures of selection in various goat breeds revealed by genome-wide SNP markers, BMC Genomics, 18(1): 229.

https://doi.org/10.1186/s12864-017-3610-0

Colli L., Milanesi M., Talenti A., Bertolini F., Chen M., Crisà A., Daly K., Del Corvo M., Guldbrandtsen B., Lenstra J., Rosen B., Vajana E., Catillo G., Joost S., Nicolazzi E., Rochat E., Rothschild M., Servin B., Sonstegard T., Steri R., Van Tassell C., Ajmone-Marsan P., Crepaldi P., and AdaptMap Consortium, 2018, Genome-wide SNP profiling of worldwide goat populations reveals strong partitioning of diversity and highlights post-domestication migration routes, Genetics Selection Evolution, 50(1): 58.

https://doi.org/10.1186/s12711-018-0422-x

Crysnanto D., Leonard A.S., Fang Z.H., and Pausch H., 2021, Novel functional sequences uncovered through a bovine multiassembly graph, Proceedings of the National Academy of Sciences, 118(20): e2101056118.

https://doi.org/10.1073/pnas.2101056118

Dai X., Bian P., Hu D., Luo F., Huang Y., Jiao S., Wang X., Gong M., Li R., Cai Y., Wen J., Yang Q., Deng W., Nanaei H., Wang Y., Wang F., Zhang Z., Rosen B., Heller R., and Jiang Y., 2023, A Chinese indicine pangenome reveals a wealth of novel structural variants introgressed from other Bos species, Genome Research, 33(8): 128-1298.

https://doi.org/10.1101/gr.277481.122

Daly K.G., Maisano Delser P., Mullin V.E., Scheu A., Mattiangeli V., Teasdale M.D., Hare A., Burger J., Verdugo M., Collins M., and others, 2018, Ancient goat genomes reveal mosaic domestication in the Fertile Crescent, Science, 361(6397): 85-88.

https://doi.org/10.1126/science.aas9411

Daly K.G., Mattiangeli V., Hare A.J., Davoudi H., Fathi H., Doost S.B., Mortensen P., Pantos A., Yeomans L., Bangsgaard P., and others, 2021, Herded and hunted goat genomes from the dawn of domestication in the Zagros Mountains, Proceedings of the National Academy of Sciences, 118(25): e2100901118.

https://doi.org/10.1073/pnas.2100901118

Denoyelle L., Talouarn E., Bardou P., Colli L., Alberti A., Danchin C., Del Corvo M., Engelen S., Orvain C., Palhière I., and others, 2021, VarGoats project: a dataset of 1159 whole-genome sequences to dissect Capra hircus global diversity, Genetics Selection Evolution, 53(1): 86.

https://doi.org/10.1186/s12711-021-00659-6

Dong Y., Xie M., Jiang Y., Xiao N., Du X., Zhang W., Tosser-Klopp G., Wang J., Yang S., and others, 2013, Sequencing and automated whole-genome optical mapping of the genome of a domestic goat (Capra hircus), Nature Biotechnology, 31: 135-141.

https://doi.org/10.1038/nbt.2478

Gao L., Gonda I., Sun H., Ma Q., Bao K., Tieman D.M., Burzynski-Chang E., Fish T., Stromberg K., and others, 2019, The tomato pan-genome uncovers new genes and a rare allele regulating fruit flavor, Nature Genetics, 51(6): 1044-1051.

https://doi.org/10.1038/s41588-019-0410-2

Gong Y., Li Y., Liu X., Ma Y., and Jiang L., 2023, A review of the pangenome: How it affects our understanding of genomic variation, selection and breeding in domestic animals, Journal of Animal Science and Biotechnology, 14(1): 73.

https://doi.org/10.1186/s40104-023-00860-1

Liao W.W., Asri M., Ebler J., Doerr D., Haukness M., Hickey G., Lu S., Lucas J., Monlong J., and others, 2023, A draft human pangenome reference, Nature, 617(7960): 312-324.

https://doi.org/10.1038/s41586-023-05896-x

Li R., Fu W., Su R., Tian X., Du D., Zhao Y., Zheng Z., Chen Q., Gao S., Cai Y., Wang X., Li J., and Jiang Y., 2019, Towards the complete goat pan-genome by recovering missing genomic segments from the reference genome, Frontiers in Genetics, 10: 1169.

https://doi.org/10.3389/fgene.2019.01169

Li X., Yang J., Shen M., He X., Liu G., Xu Y., Lv F., Yang H., Yang Y., and others, 2020, Whole-genome resequencing of wild and domestic sheep identifies genes associated with morphological and agronomic traits, Nature Communications, 11(1): 2815.

https://doi.org/10.1038/s41467-020-16485-1

Li Z., Liu X., Wang C., Li Z., Jiang B., Zhang R., Tong L., Qu Y., He S., and others, 2023b, The pig pangenome provides insights into the roles of coding structural variations in genetic diversity and adaptation, Genome Research, 33(10): 1833-1847.

https://doi.org/10.1101/gr.277638.122

Li R., Gong M., Zhang X., Wang F., Liu Z., Zhang L., Yang Q., Xu Y., Xu M., Zhang H., and others, 2023a, A sheep pangenome reveals the spectrum of structural variations and their effects on tail phenotypes, Genome Research, 33(3): 463-477.

https://doi.org/10.1101/gr.277372.12

Liu J., Shi Y., Mo D., Luo L., Xu S., and Lv F., 2024, The goat pan-genome reveals patterns of gene loss during domestication, Journal of Animal Science and Biotechnology, 15(1): 132.

https://doi.org/10.1186/s40104-023-00932-2

Lu C.D., 2023, The role of goats in the world: Society, science, and sustainability, Small Ruminant Research, 227: 107056.

https://doi.org/10.1016/j.smallrumres.2023.107056

Lu Y., Ma R., Li D., Gao Y., Sheng Z., Shi J., and He X., 2025, Genomic and molecular mechanisms of goat environmental adaptation, Biology, 14(6): 654.

https://doi.org/10.3390/biology14060654

Sasazaki S., Tomita K., Nomura Y., Kawaguchi F., Kunieda T., Shah M.K., and Mannen H., 2021, FGF5 and EPAS1 gene polymorphisms are associated with high-altitude adaptation in Nepalese goat breeds, Animal Science Journal, 92(1): e13640.

https://doi.org/10.1111/asj.13640

Nanaei H.A., Cai Y., Alshawi A., Wen J., Hussain T., Fu W., Xu N., Essa A., Lenstra J., and Jiang Y., 2023, Genomic analysis of indigenous goats in Southwest Asia reveals evidence of ancient adaptive introgression related to desert climate, Zoological Research, 44(1): 20.

https://doi.org/10.24272/j.issn.2095-8137.2022.242

Nair M.R., Sejian V., Silpa M.V., Fonsêca V.F.C., de Melo Costa C.C., Devaraj C., Krishnan G., Bagath M., Nameer P., and Bhatta R., 2021, Goat as the ideal climate-resilient animal model in tropical environment: Revisiting advantages over other livestock species, International Journal of Biometeorology, 65(12): 2229–2240.

https://doi.org/10.1007/s00484-021-02179-w

Pogorevc N., Dotsev A., Upadhyay M., Sandoval-Castellanos E., Hannemann E., Simčič M., Antoniou A., Papachristou D., Koutsouli P., and others, 2024, Whole-genome SNP genotyping unveils ancestral and recent introgression in wild and domestic goats, Molecular Ecology, 33(1): e17190.

https://doi.org/10.1111/mec.17190

Wang K., Hu H., Tian Y., Li J., Scheben A., Zhang C., Li Y., Wu J., Yang L., and others, 2021, The chicken pan-genome reveals gene content variation and a promoter region deletion in IGF2BP1 affecting body size, Molecular Biology and Evolution, 38(11): 5066-5081.

https://doi.org/10.1093/molbev/msab231

Yang J., Wang D.F., Huang J.H., Zhu Q.H., Luo L.Y., Lu R., Xie X., Salehian-Dehkordi H., Esmailizadeh A., Liu G., and Li M.H., 2024, Structural variant landscapes reveal convergent signatures of evolution in sheep and goats, Genome Biology, 25(1): 148.

https://doi.org/10.1186/s13059-024-03288-6

Zheng Z., Wang X., Li M., Li Y., Yang Z., Wang X., Pan X., Gong M., Zhang Y., and others, 2020, The origin of domestication genes in goats, Science Advances, 6(21): eaaz5216.

https://doi.org/10.1126/sciadv.aaz5216

Zhou Y., Yang L., Han X., Han J., Hu Y., Li F., Xia H., Peng L., Boschiero C., Rosen B., Bickhart D., Zhang S., Guo A., Van Tassell C., Smith T., Yang L., and Liu G., 2022, Assembly of a pangenome for global cattle reveals missing sequences and novel structural variations, providing new insights into their diversity and evolutionary history, Genome Research, 32: 1585-1601.

https://doi.org/10.1101/gr.276550.122