Literature DB >> 30981488

Variance of gametic diversity and its application in selection programs.

D J A Santos1, J B Cole2, T J Lawlor3, P M VanRaden2, H Tonhati4, L Ma5.   

Abstract

The variance of gametic diversity ( σgamete2) can be used to find individuals that more likely produce progeny with extreme breeding values. The aim of this study was to obtain this variance for individuals from routine genomic evaluations, and to apply gametic variance in a selection criterion in conjunction with breeding values to improve genetic progress. An analytical approach was developed to estimate σgamete2 by the sum of binomial variances of all individual quantitative trait loci across the genome. Simulation was used to verify the predictability of this variance in a range of scenarios. The accuracy of prediction ranged from 0.49 to 0.85, depending on the scenario and model used. Compared with sequence data, SNP data are sufficient for estimating σgamete2 Results also suggested that markers with low minor allele frequency and the covariance between markers should be included in the estimation. To incorporate σgamete2 into selective breeding programs, we proposed a new index, relative predicted transmitting ability, which better utilizes the genetic potential of individuals than traditional predicted transmitting ability. Simulation with a small genome showed an additional genetic gain of up to 16% in 10 generations, depending on the number of quantitative trait loci and selection intensity. Finally, we applied σgamete2 to the US genomic evaluations for Holstein and Jersey cattle. As expected, the DGAT1 gene had a strong effect on the estimation of σgamete2 for several production traits. However, inbreeding had a small impact on gametic variability, with greater effect for more polygenic traits. In conclusion, gametic variance, a potentially important parameter for selection programs, can be easily computed and is useful for improving genetic progress and controlling genetic diversity. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Entities:  

Keywords:  Mendelian sampling; dairy cattle; gamete; heterozygosity; selective breeding

Mesh:

Substances:

Year:  2019        PMID: 30981488     DOI: 10.3168/jds.2018-15971

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


  4 in total

1.  Breeding Top Genotypes and Accelerating Response to Recurrent Selection by Selecting Parents with Greater Gametic Variance.

Authors:  Piter Bijma; Yvonne C J Wientjes; Mario P L Calus
Journal:  Genetics       Date:  2019-11-26       Impact factor: 4.562

Review 2.  Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review.

Authors:  Miguel A Gutierrez-Reinoso; Pedro M Aponte; Manuel Garcia-Herreros
Journal:  Animals (Basel)       Date:  2021-02-25       Impact factor: 3.231

3.  Gamevar.f90: a software package for calculating individual gametic diversity.

Authors:  Daniel Jordan de Abreu Santos; John B Cole; George E Liu; Paul M VanRaden; Li Ma
Journal:  BMC Bioinformatics       Date:  2020-03-06       Impact factor: 3.169

4.  Why and How to Switch to Genomic Selection: Lessons From Plant and Animal Breeding Experience.

Authors:  Aline Fugeray-Scarbel; Catherine Bastien; Mathilde Dupont-Nivet; Stéphane Lemarié
Journal:  Front Genet       Date:  2021-07-09       Impact factor: 4.599

  4 in total

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