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Frontiers in genetics2025; 16; 1439312; doi: 10.3389/fgene.2025.1439312

The genetic diversity and population structure of native horse breeds in Xinjiang, China.

Abstract: Xinjiang is a region renowned for its rich diversity of native horse breeds, making it one of the most affluent equine genetic resource areas in China. While prized for their high adaptability and tolerance to roughage, the conservation of these native breeds faces challenges from the introduction of external breeds and industrial changes. Furthermore, the unknown population structure of Xinjiang horse breeds has hindered effective conservation efforts. Unassigned: This study presents the first comprehensive Single Nucleotide Polymorphism (SNP) analysis of seven Xinjiang native horse breeds. We utilized 10X whole-genome sequencing to assess their genetic diversity, population structure, and genetic relationships. Unassigned: Our findings revealed a high level of population genetic diversity among the Xinjiang native horse breeds. These breeds exhibited significant genetic differentiation from other horse breeds originating from Europe, Central Asia, Western Asia, and other parts of China. Evidence of frequent historical gene flow was detected, particularly among breeds in northern Xinjiang, which were shown to be more closely related to each other. Unassigned: This study elucidates the distribution patterns, evolutionary characteristics, and substantial genetic diversity of Xinjiang's native horse breeds. The results provide crucial insights into their unique genetic background and population history. These findings offer valuable theoretical support for establishing core conservation groups of local germplasm, guiding future breeding programs for new cultivars, and further exploration of the characteristics inherent to Xinjiang's native horse genetic resources.
Publication Date: 2025-11-12 PubMed ID: 41306915PubMed Central: PMC12646806DOI: 10.3389/fgene.2025.1439312Google Scholar: Lookup
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  • Journal Article

Summary

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Overview

  • This study analyzed the genetic diversity and population structure of seven native horse breeds from Xinjiang, China, using whole-genome sequencing to better understand their relationships and aid conservation efforts.

Introduction

  • Xinjiang is known for its rich diversity of native horse breeds, representing a valuable genetic resource for China.
  • These horses are notable for their adaptability and ability to thrive on rough forage, making them important for local livelihoods.
  • However, the native breeds face threats from the introduction of external horse breeds and industrialization, which may reduce genetic uniqueness and diversity.
  • Before this study, the population structure of these breeds was poorly understood, limiting targeted conservation efforts.

Methodology

  • The researchers conducted the first comprehensive study using Single Nucleotide Polymorphism (SNP) analysis to investigate genetic variation among seven native horse breeds from Xinjiang.
  • They employed 10X whole-genome sequencing technologies, which provide high-resolution genetic data by sequencing entire genomes at high coverage.
  • This method allowed them to assess genetic diversity, relationships between horse populations, and historical gene flow patterns.

Key Findings

  • High Population Genetic Diversity: The seven Xinjiang horse breeds displayed substantial genetic variation, suggesting a rich and diverse gene pool.
  • Distinct Genetic Differentiation: These native breeds were genetically distinct from horse breeds originating from Europe, Central Asia, Western Asia, and other regions of China.
  • Historical Gene Flow: Genetic data showed evidence of frequent interbreeding and gene exchange, especially among breeds from northern Xinjiang, indicating close relationships within this geographic area.
  • Population Structure: The study found clear patterns in how these breeds are related, shaped by their geographical distribution and historical interactions.

Implications and Applications

  • The research clarifies the evolutionary history and unique genetic makeup of Xinjiang’s native horses, providing a foundation for preserving their genetic identity.
  • Findings support the establishment of core conservation populations to maintain and protect local horse genetic resources effectively.
  • Results can guide breeding programs aimed at developing new cultivars that retain the important traits of Xinjiang’s native breeds.
  • The improved understanding of genetic diversity and structure may help elucidate specific breed characteristics valuable for adaptation and performance under local conditions.

Conclusion

  • This study is a significant contribution to knowledge about the genetic diversity and population structure of Xinjiang’s native horses.
  • It emphasizes the importance of conserving these breeds amid external pressures and industrial changes by leveraging genomic data for sustainable breeding and management.
  • The comprehensive genomic approach used provides a valuable model for studying other native livestock populations facing similar conservation challenges.

Cite This Article

APA
Tang C, Yang B, Dawulietihan G, Xue L, Liu S, Yalimaimaiti Y, Wang Q, Yang N, Sun X, Wang Y, Wumaier A, Khizat S, Assanbayev T, Kozhanov Z, Attokurov K, Obdunov E, Li H, Reheman A, Zhou X, Aizimu W, Iskhan K, Muhatai G. (2025). The genetic diversity and population structure of native horse breeds in Xinjiang, China. Front Genet, 16, 1439312. https://doi.org/10.3389/fgene.2025.1439312

Publication

ISSN: 1664-8021
NlmUniqueID: 101560621
Country: Switzerland
Language: English
Volume: 16
Pages: 1439312
PII: 1439312

Researcher Affiliations

Tang, Chi
  • College of Life Science and Technology, Tarim University, Alar, Xinjiang, China.
  • Xinjiang Production & Construction Corps Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Alar, Xinjiang, China.
Yang, Baoyu
  • College of Life Science and Technology, Tarim University, Alar, Xinjiang, China.
  • Xinjiang Production & Construction Corps Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Alar, Xinjiang, China.
Dawulietihan, Gulibaheti
  • Agricultural (Animal Husbandry) Development Service in Tuerhong Township, Fuyun, Xinjiang, China.
Xue, Li
  • Animal Husbandry Workstation of Fuyun County, Fuyun, Xinjiang, China.
Liu, Shuyuan
  • Animal Husbandry Workstation of Balikun County, Balikun, Xinjiang, China.
Yalimaimaiti, Yinamujiang
  • Animal Husbandry and Veterinary Station of Kalayagaqi Town, Yining, Xinjiang, China.
Wang, Qingzheng
  • Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & Construction Corps, Alar, Xinjiang, China.
Yang, Na
  • College of Life Science and Technology, Tarim University, Alar, Xinjiang, China.
  • Xinjiang Production & Construction Corps Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Alar, Xinjiang, China.
  • Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & Construction Corps, Alar, Xinjiang, China.
Sun, Xiaoyuan
  • Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & Construction Corps, Alar, Xinjiang, China.
Wang, Yaru
  • Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & Construction Corps, Alar, Xinjiang, China.
Wumaier, Ailifeire
  • Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & Construction Corps, Alar, Xinjiang, China.
Khizat, Serik
  • Physiology, Morphology and Biochemistry, Kazakh National Agrarian Research University, Almaty, Kazakhstan.
Assanbayev, Tolegen
  • Zootechnology and Veterinary Medicine, Toraighyrov University, Pavlodar, Kazakhstan.
Kozhanov, Zhassulan
  • Horse Breeding Department, Kazakh Research Institute of Livestock and Forage Production, Almaty, Kazakhstan.
Attokurov, Kursantbek
  • Osh State University, Osh, Kyrgyzstan.
Obdunov, Elmurat
  • Osh State University, Osh, Kyrgyzstan.
Li, Hangsen
  • Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & Construction Corps, Alar, Xinjiang, China.
Reheman, Aikebaier
  • Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & Construction Corps, Alar, Xinjiang, China.
Zhou, Xiaoling
  • Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & Construction Corps, Alar, Xinjiang, China.
Aizimu, Wumaierjiang
  • Xinjiang Production & Construction Corps Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Alar, Xinjiang, China.
  • Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & Construction Corps, Alar, Xinjiang, China.
Iskhan, Kairat
  • Physiology, Morphology and Biochemistry, Kazakh National Agrarian Research University, Almaty, Kazakhstan.
Muhatai, Gemingguli
  • College of Life Science and Technology, Tarim University, Alar, Xinjiang, China.
  • Xinjiang Production & Construction Corps Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Alar, Xinjiang, China.
  • Key Laboratory of Tarim Animal Husbandry Science and Technology, Xinjiang Production & Construction Corps, Alar, Xinjiang, China.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

This article includes 33 references
  1. Annie C., Dexin C.. Results of field research on ancient stonework in the river valleys of bortala and ili in Western tian Shan (xinjiang, China). Asian Perspect 59, 385–420.
    doi: 10.1353/asi.2020.0019google scholar: lookup
  2. Cai D., Tang Z., Han L., Speller C. F., Yang D. Y., Ma X.. Ancient DNA provides new insights into the origin of the Chinese domestic horse. J. Archaeol. Sci. 36, 835–842.
    doi: 10.1016/j.jas.2008.11.006google scholar: lookup
  3. Castaneda C., Juras R., Khanshour A., Randlaht I., Wallner B., Rigler D.. Population genetic analysis of the Estonian native horse suggests diverse and distinct genetics, ancient origin and contribution from unique patrilines. Genes (Basel) 10, 629.
    doi: 10.3390/genes10080629pmc: PMC6722507pubmed: 31434327google scholar: lookup
  4. Chang C. C., Chow C. C., Tellier L. C., Vattikuti S., Purcell S. M., Lee J. J.. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 4, 7.
    doi: 10.1186/s13742-015-0047-8pmc: PMC4342193pubmed: 25722852google scholar: lookup
  5. Cosgrove E. J., Sadeghi R., Schlamp F., Holl H. M., Moradi-Shahrbabak M., Miraei-Ashtiani S. R.. genome diversity and the origin of the arabian horse. Sci. Rep. 10, 9702.
    doi: 10.1038/s41598-020-66232-1pmc: PMC7298027pubmed: 32546689google scholar: lookup
  6. DePristo M. A., Banks E., Poplin R., Garimella K. V., Maguire J. R., Hartl C.. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498.
    doi: 10.1038/ng.806pmc: PMC3083463pubmed: 21478889google scholar: lookup
  7. Druml T., Baumung R., Sölkner J.. Pedigree analysis in the Austrian noriker draught horse: genetic diversity and the impact of breeding for coat colour on population structure. J. Anim. Breed. Genet. 126, 348–356.
  8. Fages A., Hanghøj K., Khan N., Gaunitz C., Seguin-Orlando A., Leonardi M.. tracking five millennia of horse management with extensive ancient genome time series. Cell 177, 1419–35.e31.
    doi: 10.1016/j.cell.2019.03.049pmc: PMC6547883pubmed: 31056281google scholar: lookup
  9. Gemingguli M., Iskhan K. R., Li Y., Qi A., Wunirifu W., Ding L. Y.. Genetic diversity and population structure of Kazakh horses (Equus caballus) inferred from mtDNA sequences. Genet. Mol. Res. 15.
    doi: 10.4238/gmr.15048618pubmed: 27808359google scholar: lookup
  10. Han H., Zhang Q., Gao K., Yue X., Zhang T., Dang R.. Y-Single nucleotide polymorphisms diversity in Chinese Indigenous horse. Asian-Australas J. Anim. Sci. 28, 1066–1074.
    doi: 10.5713/ajas.14.0784pmc: PMC4478473pubmed: 26104513google scholar: lookup
  11. Hemphill B. E., Mallory J. P.. Horse-mounted invaders from the Russo-Kazakh steppe or agricultural colonists from Western central Asia? A craniometric investigation of the Bronze Age settlement of Xinjiang. Am. J. Phys. Anthropol. 124, 199–222.
    doi: 10.1002/ajpa.10354pubmed: 15197817google scholar: lookup
  12. Huang J., Zhao Y., Shiraigol W., Li B., Bai D., Ye W.. Analysis of horse genomes provides insight into the diversification and adaptive evolution of karyotype. Sci. Rep. 4, 4958.
    doi: 10.1038/srep04958pmc: PMC4021364pubmed: 24828444google scholar: lookup
  13. Jun J., Cho Y. S., Hu H., Kim H. M., Jho S., Gadhvi P.. Whole genome sequence and analysis of the Marwari horse breed and its genetic origin. BMC Genomics 15 (Suppl. 9), S4.
    doi: 10.1186/1471-2164-15-S9-S4pmc: PMC4290615pubmed: 25521865google scholar: lookup
  14. Kalbfleisch T. S., Rice E. S., DePriest M. S., Jr., Walenz B. P., Hestand M. S., Vermeesch J. R.. Improved reference genome for the domestic horse increases assembly contiguity and composition. Commun. Biol. 1, 197.
    doi: 10.1038/s42003-018-0199-zpmc: PMC6240028pubmed: 30456315google scholar: lookup
  15. Khanshour A., Conant E., Juras R., Cothran E. G.. Microsatellite analysis of genetic diversity and population structure of Arabian horse populations. J. Hered. 104, 386–398.
    doi: 10.1093/jhered/est003pubmed: 23450090google scholar: lookup
  16. Letunic I, Bork P. Interactive Tree of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res 49, W293–W296.
    doi: 10.1093/nar/gkab301pmc: PMC8265157pubmed: 33885785google scholar: lookup
  17. Li H, Durbin R. Fast and accurate long-read alignment with Burrows-Wheeler transform. Bioinformatics 26, 589–595.
  18. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079.
  19. Librado P, Khan N, Fages A, Kusliy M A, Suchan T, Tonasso-Calvière L. The origins and spread of domestic horses from the Western Eurasian steppes. Nature 598, 634–640.
    doi: 10.1038/s41586-021-04018-9pmc: PMC8550961pubmed: 34671162google scholar: lookup
  20. Ling Y H, Ma Y H, Guan W J, Cheng Y J, Wang Y P, Han J L. Evaluation of the genetic diversity and population structure of Chinese indigenous horse breeds using 27 microsatellite markers. Anim. Genet. 42, 56–65.
  21. Liu X, Zhang Y, Li Y, Pan J, Wang D, Chen W. EPAS1 gain-of-function mutation contributes to high-altitude adaptation in Tibetan horses. Mol. Biol. Evol. 36, 2591–2603.
    doi: 10.1093/molbev/msz158pmc: PMC6805228pubmed: 31273382google scholar: lookup
  22. Mcgahern A, Bower M A M, Edwards C J, Brophy P O, Sulimova G, Zakharov I. Evidence for biogeographic patterning of mitochondrial DNA sequences in Eastern horse populations. Anim. Genet. 37, 494–497.
  23. Orlando L. The evolutionary and historical foundation of the modern horse: lessons from Ancient genomics. Annu. Rev. Genet. 54, 563–581.
  24. Petersen J L, Mickelson J R, Cothran E G, Andersson L S, Axelsson J, Bailey E. Genetic diversity in the modern horse illustrated from genome-wide SNP data. PLoS One 8, e54997.
  25. Price A L, Patterson N J, Plenge R M, Weinblatt M E, Shadick N A, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909.
    doi: 10.1038/ng1847pubmed: 16862161google scholar: lookup
  26. Price M N, Dehal P S, Arkin A P. FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol. Biol. Evol. 26, 1641–1650.
    doi: 10.1093/molbev/msp077pmc: PMC2693737pubmed: 19377059google scholar: lookup
  27. Raj A, Stephens M, Pritchard J K. fastSTRUCTURE: variational inference of population structure in large SNP data sets. Genetics 197, 573–589.
    doi: 10.1534/genetics.114.164350pmc: PMC4063916pubmed: 24700103google scholar: lookup
  28. Rosenberg N A, Pritchard J K, Weber J L, Cann H M, Kidd K K, Zhivotovsky L A. Genetic structure of human populations. Science 298, 2381–2385.
    doi: 10.1126/science.1078311pubmed: 12493913google scholar: lookup
  29. Schubert M, Jónsson H, Chang D, Der Sarkissian C, Ermini L, Ginolhac A. Prehistoric genomes reveal the genetic foundation and cost of horse domestication. Proc. Natl. Acad. Sci. U. S. A. 111, E5661–E5669.
    doi: 10.1073/pnas.1416991111pmc: PMC4284583pubmed: 25512547google scholar: lookup
  30. Spielman D, Brook B W, Richard F. Most species are not driven to extinction before genetic factors impact them. Proc. Natl. Acad. Sci. U. S. A. 101, 15261–15264.
    doi: 10.1073/pnas.0403809101pmc: PMC524053pubmed: 15477597google scholar: lookup
  31. Tozaki T, Ohnuma A, Kikuchi M, Ishige T, Kakoi H, Hirota KI. Rare and common variant discovery by whole-genome sequencing of 101 Thoroughbred racehorses. Sci. Rep. 11, 16057.
    doi: 10.1038/s41598-021-95669-1pmc: PMC8346562pubmed: 34362995google scholar: lookup
  32. Zhang T, Lu H, Chen C, Jiang H, Wu S. Genetic diversity of mtDNA D-loop and maternal origin of three Chinese native horse breeds. Asian-Australas J. Anim. Sci. 25, 921–926.
    doi: 10.5713/ajas.2011.11483pmc: PMC4092969pubmed: 25049645google scholar: lookup
  33. Zhang C, Ni P, Ahmad HI, Gemingguli M, Baizilaitibei A, Gulibaheti D. Detecting the population structure and scanning for signatures of selection in horses (Equus caballus) from whole-genome sequencing data. Evol. Bioinform Online 14, 1176934318775106.
    doi: 10.1177/1176934318775106pmc: PMC5990873pubmed: 29899660google scholar: lookup

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