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Genes2025; 16(3); 294; doi: 10.3390/genes16030294

Identification of Genetic Relationships and Group Structure Analysis of Yanqi Horses.

Abstract: The Yanqi horse is a distinguished local breed in China, known for its robust physique and strong adaptability. However, due to insufficient breeding populations and a loosely structured breeding system, the number of Yanqi horses has been declining annually. To protect its genetic resources and develop scientific breeding strategies, this study aimed to analyze the genetic diversity, parentage relationships, and genetic structure of the Yanqi horse conservation population using microsatellite markers. A total of 117 Yanqi horses were selected for genotyping analysis using 16 microsatellite markers. Genetic diversity parameters (e.g., allele number, heterozygosity, F-statistics) were calculated using GeneAIEX (v.6.503) and Fstat software (v.2.9.4). Parentage analysis was conducted using Cervus software. Bayesian clustering analysis was performed using STRUCTURE software (v.2.3.4), and a phylogenetic tree was constructed based on Nei's genetic distance to reveal the population genetic structure. A total of 191 alleles were detected, with an average allele number of 11.969, observed heterozygosity of 0.481, and expected heterozygosity of 0.787. Parentage testing showed a cumulative exclusion probability (CEP) of 0.9652999 when one parent's genotype was known and 0.9996999 when both parents' genotypes were known, achieving an accuracy of 99%. Genetic differentiation analysis revealed moderate genetic divergence among populations (FST = 0.128) and moderate inbreeding levels (FIS = 0.396). Bayesian clustering analysis (K = 4) indicated that the Yanqi horse population could be divided into four genetic clusters, reflecting the impact of geographical isolation on genetic structure. The Yanqi horse conservation population exhibits moderate genetic diversity, high accuracy in parentage identification, and moderate genetic differentiation and inbreeding. The findings provide a scientific basis for the conservation and sustainable utilization of Yanqi horse genetic resources. Future efforts should focus on strengthening conservation measures, optimizing breeding strategies, and further investigating the genetic background using genomic technologies to ensure the sustainable development of the Yanqi horse population.
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Publication Date: 2025-02-27 PubMed ID: 40149446PubMed Central: PMC11941870DOI: 10.3390/genes16030294Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This study explores the genetic diversity, relationships, and the structure of the Yanqi horse population in China using microsatellite markers. The aim is to provide the basis for maintaining and preserving this breed, which is under threat due to a diminishing population and poorly structured breeding systems.

Study Sample and Data Collection

  • The study focused on 117 Yanqi horses, a breed native to China known for its resilience and good physique.
  • Genotypic data from these horses were obtained using 16 microsatellite markers, which are DNA sequences that allow genetic comparison and diversity analysis.
  • Through this, a total of 191 alleles (variants of a gene) were detected, which served as the basis for assessing genetic variation, parentage relationships, and the overall genetic structure within the Yanqi horse population.

Genetic Diversity and Parentage Analysis

  • Using the collected data, measures of genetic diversity such as allele number, observed heterozygosity (actual genetic diversity in the population) and expected heterozygosity (expected genetic diversity, assuming no evolutionary influences) were calculated.
  • The researchers were also able to conduct parentage testing, achieving an accuracy of 99%. This high accuracy in identifying parent-offspring relationships is important for maintaining the breed and designing effective breeding programs.

Genetic Differentiation and Structure Analysis

  • The study found moderate genetic differentiation among populations, revealed by a measure called the F-statistics – a parameter used in population genetics to assess genetic divergence and inbreeding.
  • Additionally, the researchers conducted a Bayesian clustering analysis to determine the number of unique genetic groups within the Yanqi horse population. This analysis suggested that the population can be divided into four genetic clusters, indicating the effect of geographical isolation on the breed’s genetic structure.
  • A phylogenetic tree, or a “family-tree” of the populations, was also constructed. This revealed the population genetic structure in more detail, helping researchers understand the genetic relationships among different Yanqi horse groups.

Implications and Future Directions

  • The findings from this study can help develop effective strategies for conserving the Yanqi horse population and ensuring its sustainable development by preserving its genetic diversity.
  • To this end, the study recommends strengthening conservation measures, optimizing breeding strategies, and using advanced genomic technologies for more detailed investigations into the breed’s genetic background.

Cite This Article

APA
Wang Y, Tang C, Xue P, Yang N, Sun X, Serik K, Assanbayer T, Shamekova M, Kozhanov Z, Sapakhova Z, Khurramovich JK, Zhou X, Kairat I, Muhatai G. (2025). Identification of Genetic Relationships and Group Structure Analysis of Yanqi Horses. Genes (Basel), 16(3), 294. https://doi.org/10.3390/genes16030294

Publication

Genes
ISSN: 2073-4425
NlmUniqueID: 101551097
Country: Switzerland
Language: English
Volume: 16
Issue: 3
PII: 294

Researcher Affiliations

Wang, Yaru
  • College of Animals Science and Technology, Tarim University, Alar 843300, China.
  • Key Laboratory of Tarim Basin Biological Resources Protection and Utilization, Tarim University, Alar 843300, China.
  • Key Laboratory of Tarim Livestock Science and Technology Corps, Tarim University, Alar 843300, China.
Tang, Chi
  • College of Animals Science and Technology, Tarim University, Alar 843300, China.
  • Key Laboratory of Tarim Basin Biological Resources Protection and Utilization, Tarim University, Alar 843300, China.
Xue, Pengfei
  • College of Animals Science and Technology, Tarim University, Alar 843300, China.
  • Key Laboratory of Tarim Livestock Science and Technology Corps, Tarim University, Alar 843300, China.
Yang, Na
  • College of Animals Science and Technology, Tarim University, Alar 843300, China.
  • Key Laboratory of Tarim Basin Biological Resources Protection and Utilization, Tarim University, Alar 843300, China.
  • Key Laboratory of Tarim Livestock Science and Technology Corps, Tarim University, Alar 843300, China.
Sun, Xiaoyuan
  • College of Animals Science and Technology, Tarim University, Alar 843300, China.
  • Key Laboratory of Tarim Basin Biological Resources Protection and Utilization, Tarim University, Alar 843300, China.
  • Key Laboratory of Tarim Livestock Science and Technology Corps, Tarim University, Alar 843300, China.
Serik, Khizat
  • Physiology, Morphology and Biochemistry, Kazakh National Agrarian Research University, Almaty 050010, Kazakhstan.
Assanbayer, Tolegen
  • Zootechnology and Veterinary Medicine, Toraighyrov University, Pavlodar 140008, Kazakhstan.
Shamekova, Malika
  • Institute of Plant Biology and Biotechnology, Breeding and Biotechnology Laboratory, Almaty 050000, Kazakhstan.
Kozhanov, Zhassulan
  • Horse Breeding Department, Kazakh Research Institute of Livestock and Forage Production, Almaty 050000, Kazakhstan.
Sapakhova, Zagipa
  • Institute of Plant Biology and Biotechnology, Breeding and Biotechnology Laboratory, Almaty 050000, Kazakhstan.
Khurramovich, Jurakulov Kobil
  • Animal Husbandry and Biotechnology, Samarkand State University of Veterinary Medicine, Samarkand 140100, Uzbekistan.
Zhou, Xiaoling
  • College of Animals Science and Technology, Tarim University, Alar 843300, China.
  • Key Laboratory of Tarim Livestock Science and Technology Corps, Tarim University, Alar 843300, China.
Kairat, Iskhan
  • Physiology, Morphology and Biochemistry, Kazakh National Agrarian Research University, Almaty 050010, Kazakhstan.
Muhatai, Gemingguli
  • College of Animals Science and Technology, Tarim University, Alar 843300, China.
  • Key Laboratory of Tarim Basin Biological Resources Protection and Utilization, Tarim University, Alar 843300, China.
  • Key Laboratory of Tarim Livestock Science and Technology Corps, Tarim University, Alar 843300, China.

MeSH Terms

  • Animals
  • Horses / genetics
  • Microsatellite Repeats / genetics
  • Phylogeny
  • Genetic Variation / genetics
  • China
  • Breeding
  • Genetics, Population
  • Genotype
  • Bayes Theorem
  • Alleles

Grant Funding

  • BRZD2203 / Tarim University

Conflict of Interest Statement

The authors declare no conflicts of interest.

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Citations

This article has been cited 2 times.
  1. Hou L, Sulayman A, Zeng Y, Zhou L, Aimaier A, Kader A, Shi L. Analysis of Genetic Diversity and Race Genetic Structure of Major Horse Breeds in Xinjiang, China. Animals (Basel) 2025 Sep 14;15(18).
    doi: 10.3390/ani15182690pubmed: 41007935google scholar: lookup
  2. Toishimanov M, Zhanten O, Kanat R, Beishova I, Ulyanov V, Assanbayev T, Sharapatov T, Daurov D, Daurova A, Sapakhova Z, Nametov A, Shamekova M. The Effects of the Lactation Period, Mare Age, and Foaling on the Chemical and Physical Composition of Milk from Kazakh Mares Kept Under Natural Pasture Conditions. Animals (Basel) 2025 Jun 19;15(12).
    doi: 10.3390/ani15121817pubmed: 40564365google scholar: lookup
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