Published in: دوفصلنامه علوم و فناوری دامداری، دوره: 7، شماره: 2
COI code: JR_KLST-7-2_007
Paper Language: English
How to Download This Paper
For Downloading the Fulltext of CIVILICA papers please visit the orginal Persian Section of website.
Authors Trend of bias in prediction of genomic estimated breeding values due to selective genotyping in genomic selection schemes in consecutive generationsSeyyed Hasan Hafezian - Department of Animal Science, Faculty of Animal and Aquatic Science, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
Jabar Jamali - Department of Animal Science, Faculty of Animal and Aquatic Science, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
Mohsen Gholizadeh - Department of Animal Science, Faculty of Animal and Aquatic Science, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
Alireza Ehsani - Department of Animal Science, Tarbiat Modares University, Tehran, Iran.
Abstract:The aim of this study was to investigate the trend of bias in genomic estimated breeding values (GEBVs) arising from selective genotyping of the candidate population in an ongoing selection scheme. The bias was calculated as the regression of true breeding values (TBVs) on GEBVs. A simulation study was performed under two scenarios with selection intensities (SI) of 0.798 and 1.755 for three traits with heritability (h2) of 0.1, 0.25 and 0.4 in 10 consecutive generations. Regression of TBVs on GEBVs was close to one for the first generation when selective genotyping was random, and it continuously receded from one as selection shifted to choose animals with high EBVs from generations 2 to 10. Biasedness became larger with increased SI and decreased h2. Further, biasedness increased over the generations but the rate of change in biasedness decreased dramatically after the second generation and became almost steady after generation 4 which may be due to Bulmer effect. The findings showed that scaling down the GEBVs, using a scale parameter, might help removing biasedness in generation 4 onwards.
Keywords:genomic selection, Selective genotyping, bias
COI code: JR_KLST-7-2_007
how to cite to this paper:If you want to refer to this article in your research, you can easily use the following in the resources and references section:
Hafezian, Seyyed Hasan; Jabar Jamali; Mohsen Gholizadeh & Alireza Ehsani, 2019, Trend of bias in prediction of genomic estimated breeding values due to selective genotyping in genomic selection schemes in consecutive generations, Journal of livestock science & technology 7 (2), https://www.civilica.com/Paper-JR_KLST-JR_KLST-7-2_007.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Hafezian, Seyyed Hasan; Jabar Jamali; Mohsen Gholizadeh & Alireza Ehsani, 2019)
Second and more: (Hafezian; Jamali; Gholizadeh & Ehsani, 2019)
For a complete overview of how to citation please review the following CIVILICA Guide (Citation)
The University/Research Center Information:
Type: state university
Paper No.: 5642
in University Ranking and Scientometrics the Iranian universities and research centers are evaluated based on scientific papers.
Research Info Management
Export Citation info of this paper to research management softwares
New Related Papers
- Thermodynamic- Spectrophotometric Investigation of Dye Adsorption Process Using Modified ZnO Nanoparticles
- The Effect Of Computer-mediated Communication(CMC) On Enhancing Iranian's EFL Learner's writing Skill.
- Synthesizes and Optical properties of CMK-1/SDS-Fe+ Nano porous
- Some Properties and Applications of Graphene as Single Layer of Carbon Attoms
- Radiance of trees, grass, and bare soil before/after correction for Airborne Thermal Hyperspectral Data with EELM model
The Above articles are recently indexed in the related subjects
Iran Scientific Advertisment Netword
Share this paper
WHAT IS COI?
COI is a national code dedicated to all Iranian Conference and Journal Papers. the COI of each paper can be verified online.