Literature DB >> 22192217

Novel strategies to minimize progeny inbreeding while maximizing genetic gain using genomic information.

J E Pryce1, B J Hayes, M E Goddard.   

Abstract

In this study, 3 strategies for controlling progeny inbreeding in mating plans were compared. The strategies used information from pedigree inbreeding coefficients, genomic relationships, or shared runs of homozygosity. The strategies were compared for the reduction in genetic gain and progeny inbreeding that would be expected from selected matings, and for the decrease of homozygosity of deleterious recessive alleles. Using real pedigree, genotype [43,115 single nucleotide polymorphism (SNP) markers], and estimated breeding value data from Holstein cattle, mating plans were derived for herds of 300 cows with 20 sires available for mating, replicated 50 times. Each of the 300 individuals allocated as dams were matched to 1 of 20 sires to maximize genetic merit minus the penalty for estimated progeny inbreeding, and given the restriction that the sire could not be mated to more than 10% of the cows. The strategy that used a genomic relationship matrix (GRM) was the most effective in reducing average progeny inbreeding; this strategy also resulted in fewer homozygous SNP out of 1,000 low-frequency SNP compared with the strategy using pedigree information. In the future, large numbers of cattle may be genotyped for low-density SNP panels. A GRM constructed using 3,123 SNP produced results similar to a GRM constructed using the full 43,115 SNP. These results demonstrate that using GRM information, a 1% reduction in progeny inbreeding (valued at around $5 per cow) can be made with very little compromise in the overall breeding objective. These results and the availability of low-cost, low-density genotyping make it attractive to apply mating plans that use genomic information in commercial dairy herds.
Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2012        PMID: 22192217     DOI: 10.3168/jds.2011-4254

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


  23 in total

Review 1.  Genomic prediction in animals and plants: simulation of data, validation, reporting, and benchmarking.

Authors:  Hans D Daetwyler; Mario P L Calus; Ricardo Pong-Wong; Gustavo de Los Campos; John M Hickey
Journal:  Genetics       Date:  2012-12-05       Impact factor: 4.562

2.  Identification of genomic regions associated with inbreeding depression in Holstein and Jersey dairy cattle.

Authors:  Jennie E Pryce; Mekonnen Haile-Mariam; Michael E Goddard; Ben J Hayes
Journal:  Genet Sel Evol       Date:  2014-11-18       Impact factor: 4.297

3.  Trait-specific long-term consequences of genomic selection in beef cattle.

Authors:  Haroldo Henrique de Rezende Neves; Roberto Carvalheiro; Sandra Aidar de Queiroz
Journal:  Genetica       Date:  2017-11-08       Impact factor: 1.082

4.  Genomic Prediction of Complex Traits in Perennial Plants: A Case for Forest Trees.

Authors:  Fikret Isik
Journal:  Methods Mol Biol       Date:  2022

5.  Mitigation of inbreeding while preserving genetic gain in genomic breeding programs for outbred plants.

Authors:  Zibei Lin; Fan Shi; Ben J Hayes; Hans D Daetwyler
Journal:  Theor Appl Genet       Date:  2017-03-31       Impact factor: 5.699

6.  Accuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validation.

Authors:  Hans D Daetwyler; Andrew A Swan; Julius H J van der Werf; Ben J Hayes
Journal:  Genet Sel Evol       Date:  2012-11-12       Impact factor: 4.297

7.  Genome-wide estimates of coancestry, inbreeding and effective population size in the Spanish Holstein population.

Authors:  Silvia Teresa Rodríguez-Ramilo; Jesús Fernández; Miguel Angel Toro; Delfino Hernández; Beatriz Villanueva
Journal:  PLoS One       Date:  2015-04-16       Impact factor: 3.240

8.  Characterizing homozygosity across United States, New Zealand and Australian Jersey cow and bull populations.

Authors:  Jeremy T Howard; Christian Maltecca; Mekonnen Haile-Mariam; Ben J Hayes; Jennie E Pryce
Journal:  BMC Genomics       Date:  2015-03-15       Impact factor: 3.969

9.  The effect of genomic information on optimal contribution selection in livestock breeding programs.

Authors:  Samuel A Clark; Brian P Kinghorn; John M Hickey; Julius H J van der Werf
Journal:  Genet Sel Evol       Date:  2013-10-30       Impact factor: 4.297

10.  Regions of homozygosity in the porcine genome: consequence of demography and the recombination landscape.

Authors:  Mirte Bosse; Hendrik-Jan Megens; Ole Madsen; Yogesh Paudel; Laurent A F Frantz; Lawrence B Schook; Richard P M A Crooijmans; Martien A M Groenen
Journal:  PLoS Genet       Date:  2012-11-29       Impact factor: 5.917

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.