Genome wide landscaping of copy number variations for horse inter-breed variability

Copy number variations (CNVs) have become widely acknowledged as a significant source of genomic variability and phenotypic variance. To understand the genetic variants in horses, CNVs from six Indian horse breeds, <i>namely,</i> Manipuri, Zanskari, Bhutia, Spiti, Kathiawari and Marwari were discovered using Axiom<sup>™</sup> Equine Genotyping Array. These breeds differed in agro-climatic adaptation with distinct phenotypic characters. A total of 2668 autosomal CNVs and 381 CNV regions (CNVRs) were identified with PennCNV tool. DeepCNV was employed to re-validate to get 883 autosomal CNVs, of which 9.06% were singleton type. A total of 180 CNVRs were identified after DeepCNV filtering with the estimated length of 3.12 Kb-4.90 Mb. The functional analysis showed the majority of the CNVRs genes enriched for sensory perception and olfactory receptor activity. An Equine CNVs database, EqCNVdb (http://backlin.cabgrid.res.in/eqcnvdb/) was developed which catalogues detailed information on the horse CNVs, CNVRs and gene content within CNVRs. Also, three random CNVRs were validated with real-time polymerase chain reaction. These findings will aid in the understanding the horse genome and serve as a preliminary foundation for future CNV association research with commercially significant equine traits. The identification of CNVs and CNVRs would lead to better insights into genetic basis of important traits.

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Publication Details

Journal
Animal Biotechnology
Published
2025-01-10
DOI
https://doi.org/10.1080/10495398.2024.2446251
Citations
1
Primary Topic
Genomic variations and chromosomal abnormalities
Type
article
Field-Weighted Citation Impact
1.82

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article

Genome wide landscaping of copy number variations for horse inter-breed variability

Ram Avatar Legha, Sarika Jaiswal, Dinesh Kumar, Tapas Kumar Bhattacharya et al.
1 citations
Animal Biotechnology
Genomic variations and chromosomal abnormalities
1.82
article

Genome wide landscaping of copy number variations for horse inter-breed variability

Ram Avatar Legha, Sarika Jaiswal, Dinesh Kumar, Tapas Kumar Bhattacharya, Varij Nayan, Shiv Kumar Giri, Anil Rai, Nitesh Kumar Sharma, Mir Asif Iquebal, Anuradha Bhardwaj, Yash Pal, Bibek Saha, Prashant Singh
article en
1 citations

Abstract

Copy number variations (CNVs) have become widely acknowledged as a significant source of genomic variability and phenotypic variance. To understand the genetic variants in horses, CNVs from six Indian horse breeds, <i>namely,</i> Manipuri, Zanskari, Bhutia, Spiti, Kathiawari and Marwari were discovered using Axiom<sup>™</sup> Equine Genotyping Array. These breeds differed in agro-climatic adaptation with distinct phenotypic characters. A total of 2668 autosomal CNVs and 381 CNV regions (CNVRs) were identified with PennCNV tool. DeepCNV was employed to re-validate to get 883 autosomal CNVs, of which 9.06% were singleton type. A total of 180 CNVRs were identified after DeepCNV filtering with the estimated length of 3.12 Kb-4.90 Mb. The functional analysis showed the majority of the CNVRs genes enriched for sensory perception and olfactory receptor activity. An Equine CNVs database, EqCNVdb (http://backlin.cabgrid.res.in/eqcnvdb/) was developed which catalogues detailed information on the horse CNVs, CNVRs and gene content within CNVRs. Also, three random CNVRs were validated with real-time polymerase chain reaction. These findings will aid in the understanding the horse genome and serve as a preliminary foundation for future CNV association research with commercially significant equine traits. The identification of CNVs and CNVRs would lead to better insights into genetic basis of important traits.

Animal BiotechnologyVol. 36(1)
Indian Agricultural Statistics Research Institute (IN), National Research Centre on Equines (IN), Maharaja Engineering College (IN), Central Institute for Research on Buffaloes (IN), Indian Agricultural Research Institute (IN)
Indian Council of Agricultural Research, Indian Agricultural Research Institute, Ministry of Agriculture and Farmers Welfare, ICAR-Indian Agricultural Statistics Research Institute
Climate action
Openalex Percentile: Top 19%
Genomic variations and chromosomal abnormalities
1.82
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