Identification on novel locus of dairy traits of Kazakh horse in Xinjiang.
Abstract: The utility of high-density single nucleotide polymorphism (SNP) data help to accurately identify genomic regions that have undergone positive selection. In this study, the Affymetrix Equine 670 K high-density SNP array was used to genotype Kazakh and Yili horse population. After quality control, 370,227 autosomal SNPs were used to detect selection signatures by using global fixation index (F) and cross-population extended haplotype homozygosity (XP-EHH). The database of Ensemble, Genecards, and NCBI were used to make gene annotation and functional analysis. The results showed that there were 134 candidate SNPs overlapped between F and XP-EHH in Kazakh horse. We also discovered some potential selective sweep regions associated with milk trait, including NUMB, LGALS2, ADCY8, SLC25A30, and CA8 genes. New findings from this research have potential value for milk traits selecting in horse.
Copyright © 2018 Elsevier B.V. All rights reserved.
Publication Date: 2018-07-03 PubMed ID: 30257803DOI: 10.1016/j.gene.2018.07.009Google Scholar: Lookup
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- Journal Article
Summary
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This research explores the use of high-density single nucleotide polymorphism (SNP) data to identify genomic regions in the Kazakh horse breed that are linked to dairy traits.
Introduction and Methodology
- This study utilizes high-density SNP data, which is basically a type of genetic variation among species, to identify specific genomic regions in the Kazakh horse breed that have undergone positive selection – meaning they have traits that promote survival and reproduction. The data used in the research represents genetic variances at a single position in genomic DNA.
- The researchers used an Affymetrix Equine 670K high-density SNP array to genotype, or identify the genes of, the Kazakh and Yili horse populations.
- After quality control measures, 370,227 autosomal SNPs – those not occurring in either sex chromosome – were leveraged to detect selection signatures. These signatures can indicate specific traits that have been favorable and thus selected over many generations.
- Selection signatures were detected using two primary methods: the global fixation index (F) which measures the diversity reduction due to genetic drift, and the cross-population extended haplotype homozygosity (XP-EHH) which captures selective sweeps that are close to fixation.
- Databases like Ensemble, Genecards, and the National Center for Biotechnology Information (NCBI) were used for gene annotation (identifying and documenting the individual genes) and functional analysis (studying the role and function of the genes).
Findings & Conclusion
- The research found 134 candidate SNPs that were consistent between F and XP-EHH in the Kazakh horse breed. This suggests that these SNPs are part of selection signatures in this breed and could be linked to positive selection traits.
- The study also unearthed potential selective sweep regions associated with milk traits. These are essentially regions of the genome where advantageous traits sweep across a population. In this study, these included the NUMB, LGALS2, ADCY8, SLC25A30, and CA8 genes.
- The findings of the study are valuable as they could have potential application in selecting horses for milk traits during breeding. This is especially relevant for cultures where horse milk plays an important nutritional and symbolic role.
Cite This Article
APA
Liu LL, Fang C, Liu WJ.
(2018).
Identification on novel locus of dairy traits of Kazakh horse in Xinjiang.
Gene, 677, 105-110.
https://doi.org/10.1016/j.gene.2018.07.009 Publication
Researcher Affiliations
- Xinjiang Agricultural University, Urumqi, Xinjiang 830052, China.
- Xinjiang Agricultural University, Urumqi, Xinjiang 830052, China.
- Xinjiang Agricultural University, Urumqi, Xinjiang 830052, China. Electronic address: lwj_ws@163.com.
MeSH Terms
- Animals
- Female
- Genetics, Population / methods
- Genomics / methods
- Genotype
- Haplotypes
- Horses / genetics
- Lactation / genetics
- Milk
- Molecular Sequence Annotation / methods
- Phenotype
- Polymorphism, Single Nucleotide
- Quantitative Trait Loci / genetics
- Selection, Genetic
Citations
This article has been cited 9 times.- Dlamini NM, Dzomba EF, Magawana M, Ngcamu S, Muchadeyi FC. Linkage Disequilibrium, Haplotype Block Structures, Effective Population Size and Genome-Wide Signatures of Selection of Two Conservation Herds of the South African Nguni Cattle. Animals (Basel) 2022 Aug 19;12(16).
- Sun J, Chen T, Zhu M, Wang R, Huang Y, Wei Q, Yang M, Liao Y. Whole-genome sequencing revealed genetic diversity and selection of Guangxi indigenous chickens. PLoS One 2022;17(3):e0250392.
- Chen ZH, Xu YX, Xie XL, Wang DF, Aguilar-Gómez D, Liu GJ, Li X, Esmailizadeh A, Rezaei V, Kantanen J, Ammosov I, Nosrati M, Periasamy K, Coltman DW, Lenstra JA, Nielsen R, Li MH. Whole-genome sequence analysis unveils different origins of European and Asiatic mouflon and domestication-related genes in sheep. Commun Biol 2021 Nov 18;4(1):1307.
- Sun T, Shen J, Achilli A, Chen N, Chen Q, Dang R, Zheng Z, Zhang H, Zhang X, Wang S, Zhang T, Lu H, Ma Y, Jia Y, Capodiferro MR, Huang Y, Lan X, Chen H, Jiang Y, Lei C. Genomic analyses reveal distinct genetic architectures and selective pressures in buffaloes. Gigascience 2020 Feb 1;9(2).
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- Diao S, Huang S, Chen Z, Teng J, Ma Y, Yuan X, Chen Z, Zhang H, Li J, Zhang Z. Genome-Wide Signatures of Selection Detection in Three South China Indigenous Pigs. Genes (Basel) 2019 May 7;10(5).
- Niyazbekova Z, Xu Y, Qiu M, Wang HP, Primkul I, Nanaei HA, Ussenbekov Y, Kassen K, Liu Y, Gao CY, Akhmetsadykova S, Ruzikulov N, Jiang Y, Cai YD. Whole-genome sequencing reveals genetic architecture and selection signatures of Kazakh cattle. Zool Res 2025 Mar 18;46(2):301-311.
- Assanbayev T, Akilzhanov R, Sharapatov T, Bektayev R, Samatkyzy D, Karabayev D, Gabdulkayum A, Daniyarov A, Rakhimova S, Kozhamkulov U, Sarbassov D, Akilzhanova A, Kairov U. Whole genome sequencing and de novo genome assembly of the Kazakh native horse Zhabe. Front Genet 2024;15:1466382.
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