2021
DOI: 10.1111/jbg.12649
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Performance of using opposing homozygotes for paternity testing in Japanese Black cattle

Abstract: Genome-wide single nucleotide polymorphism (SNP) markers in Japanese Black cattle enable genomic prediction and verifying parent-offspring relationships.We assessed the performance of opposing homozygotes (OH) for paternity testing in Japanese Black cattle, using SNP genotype information of 50 sires and 3,420 fattened animals, 1,945 of which were fathered by the 50 genotyped sires.The number of OH was counted for each sire-progeny pair in 28,764 SNPs with minor allele frequencies of ≥0.05 in this population. A… Show more

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Cited by 7 publications
(7 citation statements)
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“…Figure 1 shows a histogram of MAFs in the 575 cows for the 36,426 SNP markers used in the ssGBLUP approach. The shape of the histogram is similar to those in previous studies on different Japanese Black cattle populations [37][38][39]; that is, the proportion of SNPs with low MAFs was slightly greater than that of the others. The ET center introduces cows from various parts of Japan to meet a wide demand of embryo buyers, which might confer results on the MAF distribution similar to those in previous studies.…”
Section: Comparing a And G Matrices For The 575 Cowssupporting
confidence: 82%
“…Figure 1 shows a histogram of MAFs in the 575 cows for the 36,426 SNP markers used in the ssGBLUP approach. The shape of the histogram is similar to those in previous studies on different Japanese Black cattle populations [37][38][39]; that is, the proportion of SNPs with low MAFs was slightly greater than that of the others. The ET center introduces cows from various parts of Japan to meet a wide demand of embryo buyers, which might confer results on the MAF distribution similar to those in previous studies.…”
Section: Comparing a And G Matrices For The 575 Cowssupporting
confidence: 82%
“…GCA I,popB , GCX I,popB , GCY I,popB , and GCM I,popB of each G1 mouse to G8 population were calculated using pedigree information with errors. According to estimated pedigree error rates by previous studies (e.g., [17][18][19]), the error size was set to 1%, 2%, 4%, 8%, and 16% of the total number of known parents (Table 2). Within the same error rate, we ran this simulation for 10,000 iterations to obtain the root mean squared error (RMSE) of the average genetic contributions calculated with and without pedigree errors.…”
Section: Discussionmentioning
confidence: 99%
“…Pedigree errors could have effects not only on genetic diversity evaluation but also on genetic parameter estimation, breeding value prediction, evaluating the degree of inbreeding and inferring inbreeding depression, and so on (e.g., [20,21,64]). Thus, efforts should be still paid to collect and accumulate accurate pedigree information (e.g., [19,65,66]). 1 GCA I,popB , GCX I,popB , GCY I,popB , and GCM I,popB average genetic contribution of individual I to target population B with respect to genes on autosomes, X chromosome, Y chromosome, and mitochondrial DNA, respectively.…”
Section: Effect Of Pedigree Errors On Genetic Contribution Calculationmentioning
confidence: 99%
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“…The quality of imputation using this reference population was valid for genomic prediction and genome-wide association study [ 35 , 36 ]. Moreover, several studies previously evaluated the genetic diversity and structure in Japanese Black cattle using BovineSNP50 BeadChip or GGP BovineLD v4.0 [ 37 39 ]. All SNP were filtered for call rate < 95%, minor allele frequency (MAF) < 0.01 and extreme deviation from Hardy–Weinberg equilibrium ( p < 0.0001).…”
Section: Methodsmentioning
confidence: 99%