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Bovinesnp50v2

Manufactured by Illumina
Sourced in United States

The Illumina BovineSNP50v2 is a high-throughput genotyping microarray designed for the analysis of single nucleotide polymorphisms (SNPs) in bovine species. The product provides researchers with a comprehensive and efficient tool for genetic analysis and genome-wide association studies in cattle.

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5 protocols using bovinesnp50v2

1

Bovine SNP Genotyping Quality Control

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The genotypic dataset included 69,559 animals genotyped using a 50 K SNP panel (54,609 SNP markers) of an imputed SNP set similar to the Illumina BovineSNP50V2 and Illumina BovineSNP50V3 (Illumina, Inc., San Diego, CA, USA), designed for commercial purposes. Markers with minor allele frequency (MAF) < 0.01, call rate < 0.90, difference between observed and expected heterozygosity > 0.15 (i.e., extreme departure from Hardy-Weinberg equilibrium), and not present in the pseudo-autosomal region (PAR) in the X chromosome were removed from the genotypic data as part of the quality control (QC). PAR was considered the region above BTAX:133,300,518 bp [24 (link)]. Additionally, animals with call rates lower than 0.90 were also removed. The QC in the genotypic data was done using the PREGSf90 software from the BLUPf90 family software [25 ]. After QC, 42,633 markers and 69,437 animals were kept for further analyses.
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2

Genotyping and DNA Extraction Protocol for 124,364 Animals

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DNA was extracted either from ear-punch tissue samples or blood samples for the 124,364 animals included in our study. These samples were processed to extract DNA at GeneMark (Hamilton, New Zealand) using Qiagen BioSprint kits, or at GeneSeek (Lincoln, NE, USA) using the Life Technologies’ MagMAX system. Genotyping was performed using a variety of single nucleotide polymorphism (SNP) arrays including GeneSeek GGPv1 (8729 SNPs), GGPv2 (20,012 SNPs), GGPv2.1 (20,015 SNPs), GGPv3 (31,813 SNPs), GGPv3.1 (31,945 SNPs), GGPv4 (37,092 SNPs), GGP50kv1 (48,156 SNPs), GGP50kv1.1 (48,161 SNPs), Illumina BovineSNP50v1 (53,126 SNPs), Illumina BovineSNP50v2 (53,629 SNPs), or the BovineHD (772,235 SNPs) chips.
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3

Unified Bovine Genotypes for Genomic Prediction

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The LR data included single nucleotide polymorphism (SNP) marker genotypes from 1,080 cows and 427 bulls provided by repositories of the Russian Research Institute of Farm Animal Genetics and Breeding and LLC Laboratory Genome (Saint‐Petersburg, Russia). Both Illumina BovineSNP50v2 and IDBv3 arrays (Illumina, San‐Diego, USA) were used for genotyping. Genotyped cows were from 13 LR herds. The average (SD) number of samples per herd was 82 (21). The DFS data had 414 bull genotypes from Illumina BovineSNP50 chip provided by NAV. The DFS genotypes were imputed and had passed quality control in the official NAV HOL genomic evaluations (https://www.nordicebv.info/). The LR and DFS genotypes were synchronized to have identical reading patterns (i.e. coding). Imputation was performed to unify genotypes and fill‐in missing markers. Quality control of genotypes was performed using the following criteria: call rate >95% and minor allele frequency >5%. After processing 43,194 SNP markers remained for the genomic prediction.
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4

Bovine Genotyping and SNP Selection

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Blood samples of 2,942 cows and semen samples of 383 bulls (Table 1) were used to extract the DNA by routine procedures. After that, the DNAs were quantified and genotyped using the BovineSNP50 v2 (Illumina, Inc., San Diego CA). The rate of missing genotypes was lower than 10% in all individuals. The SNPs were removed from dataset if it exhibited: 1) a call rate less than 90%; 2) minor allele frequency (MAF) less than 5%; 3) Fisher’s exact test p-value for Hardy-Weinberg Equilibrium (HWE) greater than or equal to 1 × 10−6; and 4) chromosome and position were unknown.
Of the total 54,609 SNPs, 42,307 on the 30 bovine chromosomes satisfied these selection criteria. The number of SNPs varied among chromosomes, with Bos Taurus autosome 1(BTA1) having the largest number of SNPs (2,711) and BTA 27 and BTA 28 having the fewest number of SNPs (778). The distribution of the minor allele frequency (MAF), heterozygous rate, linkage disequilibrium (LD) changed by marker distance and the average marker distance were shown in Fig 1.
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5

High-Density Bovine Genome Imputation

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Genotypic data were obtained using two SNP panels: BovineSNP50 v2 and BovineSNP50 v3 (Illumina Inc., USA). These two SNP panels were imputed to BovineSNP50 version 3 using Fimpute version 2.2 [12 ]. After excluding unmapped SNPs and SNPs on sex chromosomes, the available number of SNP markers was 54,931. After performing marker quality control, genotypes at each locus were excluded based on the following criteria: average call rate lower than 0.90; minor allele frequency less than 0.01; markers not in Hardy–Weinberg equilibrium, with a chi-square value (χ2) greater than 95%; and SNPs in extreme linkage disequilibrium (LD, r2 >0.99). After editing, 50,765 SNP genotypes were available for analysis. Furthermore, genotyped animals were excluded from analysis based on the following criteria: duplicate animals, twin animals, and animals that failed parentage tests. Duplicate animals and twin animals were removed based on marker call rates. Furthermore, genotype identification that could not be matched to the corresponding animal in the phenotypic data set was removed from a total of 2,032 Holstein dairy cattle. Finally, for ss-GBLUP for all traits, the genotype data set comprised 1,919 animals, whereas for Bayes-B, the number of animals available for MY305, FY305, and PY305 was 963, 943, and 946, respectively.
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