China possesses highly diversified and adapted indigenous goat breeds, which are widely distributed across various climatic zones, such as Tibetan goat (TBG) in Plateau Alpine Climate Zone, Xinjiang goat (XJG) in Temperate Continental Climate Zone, Jining grey goat (JNG) in Temperate Monsoon Climate Zone, Huanghuai goat (HHG) in Subtropical Monsoon Climate Zone, Hainan Black goat (HNG) adapted to the Tropical Monsoon Climate Zone. At the same time, these indigenous breeds demonstrate unique characteristics, such as high cashmere yield of Liaoning cashmere goat (LNC) (Meng et al., 2022), disease resistance of HNG (Chen et al., 2022), superior-quality brush hair produced by Yangtze River Delta white goat (YRD) and high prolificacy of JNG. A comprehensive assessment and understanding of the population structure of indigenous goat breeds is very important for the effective management of genetic resources and the sustainable breed breeding (Asroush et al., 2018). Various types of genetic markers were used to investigate the genetic structure of Chinese goat populations. In previous studies, low density microsatellite markers were used to analyze the genetic structure of indigenous Chinese goat breeds and provide a preliminary description of the population structure of indigenous goats (Wei et al., 2014; Liu et al., 2019). Later, single nucleotide polymorphism (SNP) chips were used to analyze the genetic structure of goat breeds, which provided 45,452-537,145 SNPs of genetic variation across the whole genome of goats (Tosser-Klopp et al., 2014; Talenti et al., 2018; Berihulay et al., 2019; Islam et al., 2019; Oget et al., 2019; Wang et al., 2022; Nantongo et al., 2024). However, these studies only focused on few Chinese indigenous breeds, such as the research of the selection signatures, introgression and population structure of 36 worldwide goat breeds (including 7 Chinese breeds), analyses of the genetic diversity of 6 Chinese goat breeds, and study of the population structure of three Chinese goat breeds (Berihulay et al., 2019; Islam et al., 2020; Wang et al., 2022). With the rapid development of second-generation sequencing technology and the reduction of sequencing cost, whole-genome sequencing(WGS) data have been applied to the analysis of genetic diversity and population structure of goat (Chen et al., 2021; Li et al., 2024; Liu et al., 2024), cattle (Xu et al., 2024), pig (Zhang et al., 2022), chickens (Zhi et al., 2023) and duck (Feng et al., 2021), providing genome-wide genetic variation at all loci and further enhancing the power of high throughput. Xiong et al. (2022) performed the genetic diversity and genetic structure analysis based on WGS data of 8 goat breeds worldwide, including 5 Chinese breeds. Li et al. (2023) researched the genetic domestication and selection signal analysis based on WGS data of 15 goat breeds from China, Nepal and Pakistan, including 9 Chinese breeds. However, systematic genetic analysis of indigenous goat breeds across China remains to be fully elucidated.

In recent decades, the conservation of indigenous animal breeds has gained increasing recognition for its importance. In 2007, the Food and Agriculture Organization (FAO) established the Global Plan of Action for Animal Genetic Resources (Hoffmann et al., 2011), which has since become one of the most significant frameworks guiding the conservation and sustainable use of these resources at global, regional, and national levels. Despite these international efforts, environmental factors and artificial selection have led to a reduction in the effective population size of indigenous goat breeds, with many of them now facing the risk of extinction (Wang et al., 2022; Bionda et al., 2023). Conservation and maintenance of genetic diversity is a key action for biodiversity conservation to ensure the adaptive potential of these resources to respond to environmental challenges and the sustainable animal production system (Frankham, 1995; Hogg, 2024; Kumar et al., 2024). Weitzman (Weitzman, 1992, 1993) proposed the “diversity theory” to provide quantitative indicators for the protection of endangered resources by measuring the “diversity value”. In chicken (Nguyen-Phuc and Berres, 2018), pig (Gvozdanovic et al., 2019; Zhao et al., 2021a) and cattle (Canon et al., 2001; Mateus et al., 2004; Bennewitz et al., 2006; European Cattle Genetic Diversity, 2006; Tapio et al., 2006; Medugorac et al., 2011), selected neutral molecular markers such as microsatellites were used to assess the genetic diversity and investigate conservation priority. To avoid misleading conservation assessments of breeds within a given domestic animal species when relying solely on genetic distance, both between-breed and within-breed variations must be evaluated to obtain the overall genetic diversity of a multibreed population (Caballero and Toro, 2002). Furthermore, the contribution of each breed to global diversity of multibreed should be evaluated. The software MetaPop evaluates the contribution of each breed to genetic diversity by treating the multibreed population as a metapopulation and calculating the gain or loss of gene and allele diversity that would occur after the removal of each breed from the metapopulation (Pérez-Figueroa et al., 2008). The updated Metapop2 software (Lopez-Cortegano et al., 2019a), optimized with C++ and released in 2019, enables the effective analysis of large datasets based on WGS data. Priority conservation analyses based on DNA chip data have been performed on chickens (Gao et al., 2023a, b) and pigs (Shang et al., 2020; Zhao et al., 2021b; Zhang et al., 2023; Arias et al., 2024). For goats, priority conservation analysis was investigated based on DNA chip data for 36 goat breeds worldwide, including 7 Chinese breeds (Wang et al., 2022). However, systematic priority conservation analysis of goat breeds in China based on genome resequencing data has not been performed.

To systematically investigate population structure, inbreeding levels, and conservation priorities of Chinese indigenous goat breeds, this study collected whole-genome resequencing data from 25 representative breeds across 20 Chinese provinces. These breeds encompass diverse ecotypes and exhibit distinct phenotypic characteristics. This study provide genetic evidence to support scientific management of indigenous caprine populations and establish a foundation for developing optimal conservation strategies.

China, a country renowned for its rich diversity of indigenous goat breeds, has recently completed the third national survey on livestock and poultry genetic resources, a comprehensive effort spanning three years. According to the National Breed List of Livestock and Poultry Genetic Resources (2024 edition) released by the National Livestock and Poultry Genetic Resources Committee (http://www.nahs.org.cn/gk/tz/202502/t20250210_452797.htm), there are 90 nationally recognized goat breeds in China, including 69 indigenous breeds. Maintaining the genetic diversity of indigenous livestock breeds is essential for developing new breeds and adapting to potential future demands in animal production (Toro et al., 2009). Concurrently, the rapid advancement of genome sequencing technologies, coupled with the corresponding reduction in costs, has led to a significant expansion of genomic data resources (Allendorf et al., 2010), systematic evaluation of genetic architecture, inbreeding levels, and conservation priorities using genomic data resources is essential for Chinese indigenous goat breeds.

Integrative analysis of PCA, NJ tree, and Admixture results revealed four distinct genetic clusters in Chinese goat populations, demonstrating strong concordance with their geographical distributions. Notably, these findings are largely consistent with the population structure analysis of Chinese goats conducted by Wei et al. (2014) using microsatellite markers. However, our study demonstrates a more accurate alignment between genetic branches and geographical distribution. For example, the LNC, located in northern China, was assigned to the NW cluster in our analysis, whereas previous studies classified it into the southern cluster, a grouping inconsistent with its geographic distribution (Wei et al., 2014). Additionally, our study provides a more coherent grouping of breeds from geographically adjacent regions. For instance, the JNG and HHG, both native to eastern China, were grouped into the eastern cluster in our analysis, in contrast to previous research that classified them into the NW cluster, which does not reflect their true geographical distribution. These results suggest that population structure analysis based on WGS is more accurate compared to low-density microsatellite markers, owing to its comprehensive genome-wide coverage.

This study represents the first large-scale genetic analysis of Chinese indigenous goats based on WGS data. Previous studies using DNA chips and WGS data have focused on a limited number of Chinese goat breeds (Berihulay et al., 2019; Islam et al., 2019; Chang et al., 2024; Li et al., 2024; Liu et al., 2024). For example, the LNC from the north was distinctly separated from the LPY from the southwest (Islam et al., 2019), which also aligns with our results. A clear separation was observed between the JNG from the eastern and the XDB from the southeast (Liu et al., 2024), as well as between the DAG from the southeast and the JNG from the eastern (Li et al., 2024), which is in agreement with our findings. Additionally, a clear distinction was demonstrated between the GZB from the southwest and the TBG from the northwest (Chang et al., 2024), which is also consistent with our results.

Additionally, although this study includes goat samples from five distinct climate types, no significant association was observed between climate type and population structure. These findings suggest that geographical barriers (e.g., mountains) play a major role in shaping the genetic structure of indigenous goat breeds, whereas climatic factors do not appear to be determining factors. This result is consistent with findings from global studies on goat populations.

Population structure analysis demonstrated that the four genetic clusters correlate strongly with the geographical features of the regions where the breeds are distributed. Specifically, the Taihang Mountains–Qinling Mountains–Hengduan Mountains act as a natural barrier distinguishing the NW cluster from the others. This mountain system collectively forms an elongated S-shaped configuration, traversing central China along a northeast-southwest axis, consistent with the recognized role of major mountain systems in driving population divergence through physical isolation. A well-documented example is the Qinghai–Tibet Plateau, whose dramatic uplift has profoundly reshaped regional topography and facilitated allopatric divergence in adjacent areas (Zhong et al., 2022). Similarly, the Qinling Mountains, stretching over 1,500 km east-west across central China, serve as a biogeographic barrier that has driven evolutionary differentiation in numerous wildlife species between their northern and southern slopes (Yu et al., 2014; Zhong et al., 2022). Furthermore, the Hengduan Mountains separate the NW and SW clusters—a finding consistent with previous research (Wei et al., 2014). Serving as a hot spot for biodiversity and genetic variation, this region function as a significant factor in accelerated speciation (Wang et al., 2019). In parallel, the Wuling Mountains–Wu Mountains demarcate the SW and SE clusters. Stretching north–south along the central topographic axis of southern China, this range imposes a strong barrier to the distribution of various wild mammal species, leading to pronounced genetic structure within their populations (Sun et al., 2020). Finally, the Qinling Mountains–Huai River line delineates the EA and SE clusters. This line is an east-west stretching boundary in central China, formed by the Qinling Mountains and the Huai River, which defines the natural partition between North and South China (JIA). Notably, although our study included goat samples originating from five distinct climate types, no significant association was observed between climate classification and population structure. These findings collectively suggest that major mountain ranges—rather than climatic gradients—serve as the primary drivers of genetic differentiation among indigenous Chinese goat breeds. This conclusion aligns with global patterns observed in goat populations, wherein physical barriers, rather than environmental variables, emerge as the dominant factor shaping population structure (Colli et al., 2018). Extending this perspective to neighboring regions, South Asia also possesses rich goat genetic resources. Notably, although goats from Pakistan and Bangladesh show closer genetic affinity to Chinese goats compared with those from other regions (Zhang et al., 2024), Asian goat populations can be broadly divided into three major lineages, within which South Asian (e.g., Pakistani) goats remain clearly separated from East Asian (Chinese) goats (Petretto et al., 2024). Together, these results suggest the important role of biogeography in shaping the genetic structure of goat populations.

The inbreeding coefficient (F_HOM) is a critical parameter that reflects the extent of inbreeding within a breed. A high inbreeding level may reduce the adaptability of the breed to indigenous environmental conditions (Hamilton and Miller, 2016; Robinson et al., 2019; Gao et al., 2023b). In this study, the analysis of the inbreeding coefficient reveals that Southern branches exhibit higher levels of inbreeding compared to Northern branches. Specifically, the inbreeding coefficients for the SW (mean F_HOM=0.2436) and SE (mean F_HOM=0.2992) branches are significantly higher than those of the NW (mean F_HOM=0.1048) and the EA (mean F_HOM=0.1238) branches. These findings are consistent with previous studies based on DNA chip and WGS data, which have identified elevated inbreeding levels in certain Chinese goat breeds (Berihulay et al., 2019; Islam et al., 2019; Zhao et al., 2024). For instance, Berihulay et al. (2019) reported that goats from the SW branch such as the LPY (F_IS=0.014), exhibited higher inbreeding coefficients than those from the NW branch, including the XJG (F_IS=-0.014). Similarly, the goats from the EA branch, such as the GFG (F_ROH=0.19), had higher inbreeding levels than those from the NW branch, such as the LNC (F_ROH=0.162) (Islam et al., 2019). Furthermore, Zhao et al. (2024)found that the inbreeding coefficient of the JNG (F_ROH=0.0446) from EA branch was higher than that of the NMG (F_ROH=0.0263) from NW branch. The elevated inbreeding levels observed in these regions may be attributed to historical breeding practices, geographical isolation, and limited gene flow. These results suggest that future breeding programs for southern goat breeds should take into account the levels of inbreeding.

The preservation of genetic diversity is a critical component of the new Global Biodiversity Framework (Lopez-Cortegano et al., 2019a, b; Hogg, 2024). Systematic research on conservation priorities is essential to ensure the effective protection of livestock genetic resources (Zhao et al., 2021b). In this study, gene and allele diversity were used to evaluate genetic diversity. Both within breeds and between breeds diversity were considered to assess global diversity of the metapopulation, making the evaluation more appropriate for domesticated animals (Caballero and Toro, 2002).In this study, we employed large-scale WGS data of indigenous Chinese goat breeds for the first time to assess the contribution of each breed to the genetic diversity of the metapopulation. The gene diversity analysis revealed that 12 breeds made positive contributions to the HT. All of these breeds originated from the NW and EA lineages. Previous studies have shown that gene diversity is correlated with expected heterozygosity (Lacy and Ballou, 1998; Zhao et al., 2021a). The results of Wei et al. (2014) indicate that goats from the Northern and Western combined and Eastern lineages display higher expected heterozygosity, a pattern consistent with the positive contributions of NW and EA breeds to metapopulation genetic diversity observed in our study.

Researchers are committed to further optimizing conservation strategies, and previous studies have proposed that integrating genetic clustering results with conservation prioritization may generate a more accurate prioritized conservation list. In this study, we integrated the results of the four genetic clusters of indigenous Chinese goat breeds with the final Z-scores for conservation prioritization, thereby proposing an optimized recommended breed list for indigenous Chinese goats. Thus, under conditions of limited conservation funding and efforts, the recommended breed list will maximize the preservation of genetic diversity in indigenous Chinese goat breeds. While future conservation frameworks might incorporate non-genetic factors—such as socio-cultural significance and potential economic value—considerable research and development are needed before their implementation in practical breeding programs.

In this study, population structure analysis identified four distinct genetic branches among Chinese indigenous goats. Inbreeding coefficient assessment revealed significantly higher inbreeding levels in southern breeds (SE/SW) compared to northern populations (NW/EA). Genetic diversity contribution analysis enabled establishment of a prioritized conservation list, with the top three breeds identified for each branch. The integration of these genomic assessments has facilitated the development of a conservation framework and provided a scientific basis for the strategic management of the genetic resources of Chinese indigenous goats.