Literature DB >> 28527809

Accuracy of genomic predictions in Gyr (Bos indicus) dairy cattle.

S A Boison1, A T H Utsunomiya2, D J A Santos2, H H R Neves3, R Carvalheiro2, G Mészáros1, Y T Utsunomiya2, A S do Carmo4, R S Verneque4, M A Machado4, J C C Panetto4, J F Garcia5, J Sölkner1, M V G B da Silva6.   

Abstract

Genomic selection may accelerate genetic progress in breeding programs of indicine breeds when compared with traditional selection methods. We present results of genomic predictions in Gyr (Bos indicus) dairy cattle of Brazil for milk yield (MY), fat yield (FY), protein yield (PY), and age at first calving using information from bulls and cows. Four different single nucleotide polymorphism (SNP) chips were studied. Additionally, the effect of the use of imputed data on genomic prediction accuracy was studied. A total of 474 bulls and 1,688 cows were genotyped with the Illumina BovineHD (HD; San Diego, CA) and BovineSNP50 (50K) chip, respectively. Genotypes of cows were imputed to HD using FImpute v2.2. After quality check of data, 496,606 markers remained. The HD markers present on the GeneSeek SGGP-20Ki (15,727; Lincoln, NE), 50K (22,152), and GeneSeek GGP-75Ki (65,018) were subset and used to assess the effect of lower SNP density on accuracy of prediction. Deregressed breeding values were used as pseudophenotypes for model training. Data were split into reference and validation to mimic a forward prediction scheme. The reference population consisted of animals whose birth year was ≤2004 and consisted of either only bulls (TR1) or a combination of bulls and dams (TR2), whereas the validation set consisted of younger bulls (born after 2004). Genomic BLUP was used to estimate genomic breeding values (GEBV) and reliability of GEBV (R2PEV) was based on the prediction error variance approach. Reliability of GEBV ranged from ∼0.46 (FY and PY) to 0.56 (MY) with TR1 and from 0.51 (PY) to 0.65 (MY) with TR2. When averaged across all traits, R2PEV were substantially higher (R2PEV of TR1 = 0.50 and TR2 = 0.57) compared with reliabilities of parent averages (0.35) computed from pedigree data and based on diagonals of the coefficient matrix (prediction error variance approach). Reliability was similar for all the 4 marker panels using either TR1 or TR2, except that imputed HD cow data set led to an inflation of reliability. Reliability of GEBV could be increased by enlarging the limited bull reference population with cow information. A reduced panel of ∼15K markers resulted in reliabilities similar to using HD markers. Reliability of GEBV could be increased by enlarging the limited bull reference population with cow information.
Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  genomic selection; genotyping females; indicine; small population

Mesh:

Substances:

Year:  2017        PMID: 28527809     DOI: 10.3168/jds.2016-11811

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  4 in total

Review 1.  An Appropriate Genetic Approach for Improving Reproductive Traits in Crossbred Thai-Holstein Cattle under Heat Stress Conditions.

Authors:  Akhmad Fathoni; Wuttigrai Boonkum; Vibuntita Chankitisakul; Monchai Duangjinda
Journal:  Vet Sci       Date:  2022-03-28

2.  Marker density and statistical model designs to increase accuracy of genomic selection for wool traits in Angora rabbits.

Authors:  Chao Ning; Kerui Xie; Juanjuan Huang; Yan Di; Yanyan Wang; Aiguo Yang; Jiaqing Hu; Qin Zhang; Dan Wang; Xinzhong Fan
Journal:  Front Genet       Date:  2022-09-02       Impact factor: 4.772

Review 3.  Genomic Selection and Use of Molecular Tools in Breeding Programs for Indigenous and Crossbred Cattle in Developing Countries: Current Status and Future Prospects.

Authors:  Raphael Mrode; Julie M K Ojango; A M Okeyo; Joram M Mwacharo
Journal:  Front Genet       Date:  2019-01-09       Impact factor: 4.599

4.  Integrating Genetic and Genomic Analyses of Combined Health Data Across Ecotypes to Improve Disease Resistance in Indigenous African Chickens.

Authors:  Georgios Banos; Victoria Lindsay; Takele T Desta; Judy Bettridge; Enrique Sanchez-Molano; Adriana Vallejo-Trujillo; Oswald Matika; Tadelle Dessie; Paul Wigley; Robert M Christley; Peter Kaiser; Olivier Hanotte; Androniki Psifidi
Journal:  Front Genet       Date:  2020-10-09       Impact factor: 4.599

  4 in total

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