Genotype imputation accuracy of X chromosome variants in Holstein cattle based on different software and imputation strategies

The X chromosome is one of the largest in the cattle genome, but little is known about the imputation of X chromosome variants. Thus, the main objective of this study was to assess the imputation accuracy of SNPs located in the X chromosome based on different strategies. Data from 2,505 Holstein cattle were used, and the imputation was carried out in 2 steps. Step 1 consisted of imputation from 5 medium-density (MD) SNP panels to a consolidated MD SNP panel, and step 2 was based on imputation from this consolidated MD SNP panel to a high-density (HD) SNP panel. Six scenarios (S1-S6) were evaluated for imputing autosomal SNPs (S1<sup>A</sup>, S2<sup>A</sup>, S3<sup>A</sup>, S4<sup>A</sup>, S5<sup>A</sup>, S6<sup>A</sup>), as well as the entire X chromosome (S1<sup>X</sup>, S2<sup>X</sup>, S3<sup>X</sup>, S4<sup>X</sup>, S5<sup>X</sup>, S6<sup>X</sup>) and the pseudoautosomal region (PAR; S1<sup>PAR</sup>, S2<sup>PAR</sup>, S3<sup>PAR</sup>, S4<sup>PAR</sup>, S5<sup>PAR</sup>, S6<sup>PAR</sup>) and non-PAR (S1<sup>non-PAR</sup>, S2<sup>non-PAR</sup>, S3<sup>non-PAR</sup>, S4<sup>non-PAR</sup>, S5<sup>non-PAR</sup>, S6<sup>non-PAR</sup>) segments of the X chromosome. The validation population in all these scenarios had 169 females and zero (S1, S2, and S3) or 583 (S4, S5, and S6) males, whereas the reference population had 169 (S2, S5) or 392 (S1, S3, S4, S6) females and zero (S1, S4), 196 (S2, S5), or 1,361 (S3, S6) males. Two imputation software tools (Minimac and FindHap) were compared across scenarios. Step 1 provided a consolidated MD SNP panel containing 2,132 and 63,259 SNPs located on the X and autosomal chromosomes, respectively, and step 2 resulted in an HD SNP panel with 5,921 and 294,865 SNPs located on the X and autosomal chromosomes, respectively. In step 1, the lowest average allelic correlation (R) was 0.93 (S4<sup>PAR</sup>) with Minimac and 0.79 (S4<sup>PAR</sup>) with FindHap, whereas the lowest genotypic concordance rate (CR) was 95.0 (S4<sup>PAR</sup>) with Minimac and 85.0 (S4<sup>PAR</sup>) when using FindHap. In step 2, the lowest R was 0.93 (S4<sup>PAR</sup> and S4<sup>non-PAR</sup>) with Minimac and 0.66 (S4<sup>X</sup>) with FindHap, whereas the lowest CR was 96.2 (S4<sup>PAR</sup>) with Minimac and 80.3 (S4<sup>X</sup>) with FindHap. In general, all the scenarios had high imputation accuracy of the X chromosome SNPs when using the Minimac software, whereas FindHap showed better accuracy with scenarios S3 and S6. Including both males and females in the reference and validation populations increased the imputation accuracy of X chromosome variants. These findings highlight the importance of the choice of the imputation software and the need for enlarging the reference populations to increase genotype imputation accuracy of the X chromosome variants in Holstein cattle.

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Journal
Journal of Dairy Science
Published
2025-09-19
DOI
https://doi.org/10.3168/jds.2025-26715
Primary Topic
Genetic and phenotypic traits in livestock
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article
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article

Genotype imputation accuracy of X chromosome variants in Holstein cattle based on different software and imputation strategies

Luís Fernando Batista Pinto, Henrique A. Mulim, Flávio Schramm Schenkel, Hinayah Rojas de Oliveira et al.
Journal of Dairy Science
Genetic and phenotypic traits in livestock
article

Genotype imputation accuracy of X chromosome variants in Holstein cattle based on different software and imputation strategies

Luís Fernando Batista Pinto, Henrique A. Mulim, Flávio Schramm Schenkel, Hinayah Rojas de Oliveira, Luiz F. Brito, Victor Breno Pedrosa, F. Miglior, Valdecy Aparecida Rocha da Cruz, Tatiana Cortez de Souza, Tatiane S. Chud, A O Gerson
article en

Abstract

The X chromosome is one of the largest in the cattle genome, but little is known about the imputation of X chromosome variants. Thus, the main objective of this study was to assess the imputation accuracy of SNPs located in the X chromosome based on different strategies. Data from 2,505 Holstein cattle were used, and the imputation was carried out in 2 steps. Step 1 consisted of imputation from 5 medium-density (MD) SNP panels to a consolidated MD SNP panel, and step 2 was based on imputation from this consolidated MD SNP panel to a high-density (HD) SNP panel. Six scenarios (S1-S6) were evaluated for imputing autosomal SNPs (S1<sup>A</sup>, S2<sup>A</sup>, S3<sup>A</sup>, S4<sup>A</sup>, S5<sup>A</sup>, S6<sup>A</sup>), as well as the entire X chromosome (S1<sup>X</sup>, S2<sup>X</sup>, S3<sup>X</sup>, S4<sup>X</sup>, S5<sup>X</sup>, S6<sup>X</sup>) and the pseudoautosomal region (PAR; S1<sup>PAR</sup>, S2<sup>PAR</sup>, S3<sup>PAR</sup>, S4<sup>PAR</sup>, S5<sup>PAR</sup>, S6<sup>PAR</sup>) and non-PAR (S1<sup>non-PAR</sup>, S2<sup>non-PAR</sup>, S3<sup>non-PAR</sup>, S4<sup>non-PAR</sup>, S5<sup>non-PAR</sup>, S6<sup>non-PAR</sup>) segments of the X chromosome. The validation population in all these scenarios had 169 females and zero (S1, S2, and S3) or 583 (S4, S5, and S6) males, whereas the reference population had 169 (S2, S5) or 392 (S1, S3, S4, S6) females and zero (S1, S4), 196 (S2, S5), or 1,361 (S3, S6) males. Two imputation software tools (Minimac and FindHap) were compared across scenarios. Step 1 provided a consolidated MD SNP panel containing 2,132 and 63,259 SNPs located on the X and autosomal chromosomes, respectively, and step 2 resulted in an HD SNP panel with 5,921 and 294,865 SNPs located on the X and autosomal chromosomes, respectively. In step 1, the lowest average allelic correlation (R) was 0.93 (S4<sup>PAR</sup>) with Minimac and 0.79 (S4<sup>PAR</sup>) with FindHap, whereas the lowest genotypic concordance rate (CR) was 95.0 (S4<sup>PAR</sup>) with Minimac and 85.0 (S4<sup>PAR</sup>) when using FindHap. In step 2, the lowest R was 0.93 (S4<sup>PAR</sup> and S4<sup>non-PAR</sup>) with Minimac and 0.66 (S4<sup>X</sup>) with FindHap, whereas the lowest CR was 96.2 (S4<sup>PAR</sup>) with Minimac and 80.3 (S4<sup>X</sup>) with FindHap. In general, all the scenarios had high imputation accuracy of the X chromosome SNPs when using the Minimac software, whereas FindHap showed better accuracy with scenarios S3 and S6. Including both males and females in the reference and validation populations increased the imputation accuracy of X chromosome variants. These findings highlight the importance of the choice of the imputation software and the need for enlarging the reference populations to increase genotype imputation accuracy of the X chromosome variants in Holstein cattle.

Journal of Dairy ScienceVol. 108(12)
University of Nebraska–Lincoln (US), Universidade Federal da Bahia (BR), Purdue University West Lafayette (US), University of Guelph (CA)
Openalex Percentile: Top 72%
Genetic and phenotypic traits in livestock
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