Optimized Genetic Testing for Polledness in Multiple Breeds of Cattle

Many breeds of modern cattle are naturally horned, and for sound husbandry management reasons the calves frequently undergo procedures to physically remove the horns by disbudding or dehorning. These procedures are however a welfare concern. Selective breeding for polledness – absence of horns – has...

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Main Authors: Imtiaz A. S. Randhawa, Brian M. Burns, Michael R. McGowan, Laercio R. Porto-Neto, Ben J. Hayes, Ryan Ferretti, Karen M. Schutt, Russell E. Lyons
Format: Article
Language:English
Published: Oxford University Press 2020-02-01
Series:G3: Genes, Genomes, Genetics
Subjects:
Online Access:http://g3journal.org/lookup/doi/10.1534/g3.119.400866
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spelling doaj-a79d49b1637949b1a3ed294764b0d7092021-07-02T12:27:25ZengOxford University PressG3: Genes, Genomes, Genetics2160-18362020-02-0110253954410.1534/g3.119.40086613Optimized Genetic Testing for Polledness in Multiple Breeds of CattleImtiaz A. S. RandhawaBrian M. BurnsMichael R. McGowanLaercio R. Porto-NetoBen J. HayesRyan FerrettiKaren M. SchuttRussell E. LyonsMany breeds of modern cattle are naturally horned, and for sound husbandry management reasons the calves frequently undergo procedures to physically remove the horns by disbudding or dehorning. These procedures are however a welfare concern. Selective breeding for polledness – absence of horns – has been effective in some cattle breeds but not in others (Bos indicus genotypes) due in part to the complex genetics of horn phenotype. To address this problem different approaches to genetic testing which provide accurate early-in-life prediction of horn phenotype have been evaluated, initially using microsatellites (MSAT) and more recently single nucleotide polymorphism (SNP). A direct gene test is not effective given the genetic heterogeneity and large-sized sequence variants associated with polledness in different breeds. The current study investigated 39,943 animals of multiple breeds to assess the accuracy of available poll testing assays. While the standard SNP-based test was an improvement on the earlier MSAT haplotyping method, 1999 (9.69%) out of 20,636 animals tested with this SNP-based assay did not predict a genotype, most commonly associated with the Indicus-influenced breeds. The current study has developed an optimized poll gene test that resolved the vast majority of these 1999 unresolved animals, while the predicted genotypes of those previously resolved remained unchanged. Hence the optimized poll test successfully predicted a genotype in 99.96% of samples assessed. We demonstrated that a robust set of 5 SNPs can effectively determine PC and PF alleles and eliminate the ambiguous and undetermined results of poll gene testing previously identified as an issue in cattle.http://g3journal.org/lookup/doi/10.1534/g3.119.400866poll genebovinedehorninggenetic testinganimal welfaregenomic predictiongenpredshared data resources
collection DOAJ
language English
format Article
sources DOAJ
author Imtiaz A. S. Randhawa
Brian M. Burns
Michael R. McGowan
Laercio R. Porto-Neto
Ben J. Hayes
Ryan Ferretti
Karen M. Schutt
Russell E. Lyons
spellingShingle Imtiaz A. S. Randhawa
Brian M. Burns
Michael R. McGowan
Laercio R. Porto-Neto
Ben J. Hayes
Ryan Ferretti
Karen M. Schutt
Russell E. Lyons
Optimized Genetic Testing for Polledness in Multiple Breeds of Cattle
G3: Genes, Genomes, Genetics
poll gene
bovine
dehorning
genetic testing
animal welfare
genomic prediction
genpred
shared data resources
author_facet Imtiaz A. S. Randhawa
Brian M. Burns
Michael R. McGowan
Laercio R. Porto-Neto
Ben J. Hayes
Ryan Ferretti
Karen M. Schutt
Russell E. Lyons
author_sort Imtiaz A. S. Randhawa
title Optimized Genetic Testing for Polledness in Multiple Breeds of Cattle
title_short Optimized Genetic Testing for Polledness in Multiple Breeds of Cattle
title_full Optimized Genetic Testing for Polledness in Multiple Breeds of Cattle
title_fullStr Optimized Genetic Testing for Polledness in Multiple Breeds of Cattle
title_full_unstemmed Optimized Genetic Testing for Polledness in Multiple Breeds of Cattle
title_sort optimized genetic testing for polledness in multiple breeds of cattle
publisher Oxford University Press
series G3: Genes, Genomes, Genetics
issn 2160-1836
publishDate 2020-02-01
description Many breeds of modern cattle are naturally horned, and for sound husbandry management reasons the calves frequently undergo procedures to physically remove the horns by disbudding or dehorning. These procedures are however a welfare concern. Selective breeding for polledness – absence of horns – has been effective in some cattle breeds but not in others (Bos indicus genotypes) due in part to the complex genetics of horn phenotype. To address this problem different approaches to genetic testing which provide accurate early-in-life prediction of horn phenotype have been evaluated, initially using microsatellites (MSAT) and more recently single nucleotide polymorphism (SNP). A direct gene test is not effective given the genetic heterogeneity and large-sized sequence variants associated with polledness in different breeds. The current study investigated 39,943 animals of multiple breeds to assess the accuracy of available poll testing assays. While the standard SNP-based test was an improvement on the earlier MSAT haplotyping method, 1999 (9.69%) out of 20,636 animals tested with this SNP-based assay did not predict a genotype, most commonly associated with the Indicus-influenced breeds. The current study has developed an optimized poll gene test that resolved the vast majority of these 1999 unresolved animals, while the predicted genotypes of those previously resolved remained unchanged. Hence the optimized poll test successfully predicted a genotype in 99.96% of samples assessed. We demonstrated that a robust set of 5 SNPs can effectively determine PC and PF alleles and eliminate the ambiguous and undetermined results of poll gene testing previously identified as an issue in cattle.
topic poll gene
bovine
dehorning
genetic testing
animal welfare
genomic prediction
genpred
shared data resources
url http://g3journal.org/lookup/doi/10.1534/g3.119.400866
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