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      Development of nutrigenomic based precision management model for Hanwoo steers

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          Abstract

          Focusing high marble deposition, Hanwoo feedlot system uses high-energy diet over the prolonged fattening period. However, due to the individual genetic variation, around 40% of them are graded into inferior quality grades (QG), despite they utilized the same resources. Therefore, focusing on development of a nutrigenomic based precision management model, this study was to evaluated the response to the divergent selection on genetic merit for marbling score (MS), under different dietary total digestible nutrient (TDN) levels. Total of 111 calves were genotyped and initially grouped according to estimated breeding value (high and low) for marbling score (MS-EBV). Subsequently, managed under two levels of feed TDN%, over the calf period, early, middle, and final fattening periods following 2 × 2 factorial arrangement. Carcasses were evaluated for MS, Back fat thickness (BFT) and Korean beef quality grading standard. As the direct response to the selection was significant, the results confirmed the importance of initial genetic grouping of Hanwoo steers for MS-EBV. However, dietary TDN level did not show an effect ( p > 0.05) on the MS. Furthermore, no genetic-by-nutrition interaction for MS ( p > 0.05) was also observed. The present results showed no correlation response on BFT ( p > 0.05), which indicates that the selection based on MS-EBV can be used to enhance the MS without undesirable effect on BFT. Ultimate turnover of the Hanwoo feedlot operation is primarily determined by the QGs. The present model shows that the initial grouping for MS-EBV increased the proportion of carcasses graded for higher QGs (QG1 ++ and QG1 +) by approximately 20%. Moreover, there appear to be a potential to increase the proportion of QG 1 ++ animals among the high-genetic group by further increasing the dietary energy content. Overall, this precision management strategy suggests the importance of adopting an MS based initial genetic grouping system for Hanwoo steers with a subsequent divergent management based on dietary energy level.

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          Most cited references79

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          PLINK: a tool set for whole-genome association and population-based linkage analyses.

          Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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            GCTA: a tool for genome-wide complex trait analysis.

            For most human complex diseases and traits, SNPs identified by genome-wide association studies (GWAS) explain only a small fraction of the heritability. Here we report a user-friendly software tool called genome-wide complex trait analysis (GCTA), which was developed based on a method we recently developed to address the "missing heritability" problem. GCTA estimates the variance explained by all the SNPs on a chromosome or on the whole genome for a complex trait rather than testing the association of any particular SNP to the trait. We introduce GCTA's five main functions: data management, estimation of the genetic relationships from SNPs, mixed linear model analysis of variance explained by the SNPs, estimation of the linkage disequilibrium structure, and GWAS simulation. We focus on the function of estimating the variance explained by all the SNPs on the X chromosome and testing the hypotheses of dosage compensation. The GCTA software is a versatile tool to estimate and partition complex trait variation with large GWAS data sets.
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              Efficient methods to compute genomic predictions.

              P VanRaden (2008)
              Efficient methods for processing genomic data were developed to increase reliability of estimated breeding values and to estimate thousands of marker effects simultaneously. Algorithms were derived and computer programs tested with simulated data for 2,967 bulls and 50,000 markers distributed randomly across 30 chromosomes. Estimation of genomic inbreeding coefficients required accurate estimates of allele frequencies in the base population. Linear model predictions of breeding values were computed by 3 equivalent methods: 1) iteration for individual allele effects followed by summation across loci to obtain estimated breeding values, 2) selection index including a genomic relationship matrix, and 3) mixed model equations including the inverse of genomic relationships. A blend of first- and second-order Jacobi iteration using 2 separate relaxation factors converged well for allele frequencies and effects. Reliability of predicted net merit for young bulls was 63% compared with 32% using the traditional relationship matrix. Nonlinear predictions were also computed using iteration on data and nonlinear regression on marker deviations; an additional (about 3%) gain in reliability for young bulls increased average reliability to 66%. Computing times increased linearly with number of genotypes. Estimation of allele frequencies required 2 processor days, and genomic predictions required <1 d per trait, and traits were processed in parallel. Information from genotyping was equivalent to about 20 daughters with phenotypic records. Actual gains may differ because the simulation did not account for linkage disequilibrium in the base population or selection in subsequent generations.
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                Author and article information

                Journal
                J Anim Sci Technol
                J Anim Sci Technol
                J Anim Sci Technol
                jast
                Journal of Animal Science and Technology
                Korean Society of Animal Sciences and Technology
                2672-0191
                2055-0391
                May 2023
                31 May 2023
                : 65
                : 3
                : 596-610
                Affiliations
                [1 ]Division of Animal and Dairy Science, Chungnam National University , Daejeon 34134, Korea
                [2 ]Department of Animal Science, Faculty of Agriculture, University of Ruhuna , Matara 81100, Sri Lanka
                [3 ]Department of Livestock, Korea National University of Agriculture and Fisheries , Jeonju 54874, Korea
                [4 ]Hanwoo Research Institute, National Institute of Animal Science, RDA , Pyeongchang 25340, Korea
                Author notes

                # These authors contributed equally to this work.

                [* ] Corresponding author: Seung Hwan Lee, Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea. Tel: +82-42-821-5772, E-mail: slee46@ 123456korea.kr
                [* ] Corresponding author: Ki Yong Chung, Department of Livestock, Korea National University of Agriculture and Fisheries, Jeonju 54874, Korea. Tel: +82-63-238-9212, E-mail: cky95@ 123456korea.kr
                Author information
                https://orcid.org/0000-0002-5668-1920
                https://orcid.org/0000-0001-7275-7705
                https://orcid.org/0000-0002-2174-7897
                https://orcid.org/0000-0002-6530-2304
                https://orcid.org/0000-0003-3081-5916
                https://orcid.org/0000-0002-8121-4697
                https://orcid.org/0000-0002-2197-5080
                https://orcid.org/0000-0003-1508-4887
                https://orcid.org/0000-0003-0957-875X
                Article
                jast-65-3-596
                10.5187/jast.2023.e38
                10271920
                37332286
                bd5f7f5e-f1f6-413f-b325-ff7205c873f9
                © Copyright 2023 Korean Society of Animal Science and Technology

                This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 12 January 2023
                : 25 March 2023
                : 13 April 2023
                Categories
                Research Article
                Custom metadata
                2023-06-30

                feed energy level,genetic merit for marbling,hanwoo
                feed energy level, genetic merit for marbling, hanwoo

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