Literature DB >> 25549983

Improving genetic evaluation of litter size and piglet mortality for both genotyped and nongenotyped individuals using a single-step method.

X Guo, O F Christensen, T Ostersen, Y Wang, M S Lund, G Su.   

Abstract

A single-step method allows genetic evaluation using information of phenotypes, pedigree, and markers from genotyped and nongenotyped individuals simultaneously. This paper compared genomic predictions obtained from a single-step BLUP (SSBLUP) method, a genomic BLUP (GBLUP) method, a selection index blending (SELIND) method, and a traditional pedigree-based method (BLUP) for total number of piglets born (TNB), litter size at d 5 after birth (LS5), and mortality rate before d 5 (Mort; including stillbirth) in Danish Landrace and Yorkshire pigs. Data sets of 778,095 litters from 309,362 Landrace sows and 472,001 litters from 190,760 Yorkshire sows were used for the analysis. There were 332,795 Landrace and 207,255 Yorkshire animals in the pedigree data, among which 3,445 Landrace pigs (1,366 boars and 2,079 sows) and 3,372 Yorkshire pigs (1,241 boars and 2,131 sows) were genotyped with the Illumina PorcineSNP60 BeadChip. The results showed that the 3 methods with marker information (SSBLUP, GBLUP, and SELIND) produced more accurate predictions for genotyped animals than the pedigree-based method. For genotyped animals, the average of reliabilities for all traits in both breeds using traditional BLUP was 0.091, which increased to 0.171 w+hen using GBLUP and to 0.179 when using SELIND and further increased to 0.209 when using SSBLUP. Furthermore, the average reliability of EBV for nongenotyped animals was increased from 0.091 for traditional BLUP to 0.105 for the SSBLUP. The results indicate that the SSBLUP is a good approach to practical genomic prediction of litter size and piglet mortality in Danish Landrace and Yorkshire populations.

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Year:  2015        PMID: 25549983     DOI: 10.2527/jas.2014-8331

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  20 in total

1.  Genomic selection in American mink (Neovison vison) using a SSGBLUP model for size and quality traits graded on live mink.

Authors:  Trine M Villumsen; Guosheng Su; Bernt Guldbrandtsen; Torben Asp; Mogens S Lund
Journal:  J Anim Sci       Date:  2021-01-08       Impact factor: 3.159

2.  Efficacy of energy supplementation on growth performance and immune response of suckling pigs.

Authors:  Naiana Einhardt Manzke; Bruna Kuhn Gomes; Eduardo Gonçalves Xavier; Gustavo Julio Mello Monteiro de Lima
Journal:  J Anim Sci       Date:  2018-11-21       Impact factor: 3.159

3.  Using machine learning to improve the accuracy of genomic prediction of reproduction traits in pigs.

Authors:  Xue Wang; Shaolei Shi; Guijiang Wang; Wenxue Luo; Xia Wei; Ao Qiu; Fei Luo; Xiangdong Ding
Journal:  J Anim Sci Biotechnol       Date:  2022-05-17

4.  Genetic parameters and purebred-crossbred genetic correlations for growth, meat quality, and carcass traits in pigs.

Authors:  Hadi Esfandyari; Dinesh Thekkoot; Robert Kemp; Graham Plastow; Jack Dekkers
Journal:  J Anim Sci       Date:  2020-12-01       Impact factor: 3.159

5.  Genomic prediction of crossbred performance based on purebred Landrace and Yorkshire data using a dominance model.

Authors:  Hadi Esfandyari; Piter Bijma; Mark Henryon; Ole Fredslund Christensen; Anders Christian Sørensen
Journal:  Genet Sel Evol       Date:  2016-06-08       Impact factor: 4.297

6.  Genomic evaluation by including dominance effects and inbreeding depression for purebred and crossbred performance with an application in pigs.

Authors:  Tao Xiang; Ole Fredslund Christensen; Zulma Gladis Vitezica; Andres Legarra
Journal:  Genet Sel Evol       Date:  2016-11-25       Impact factor: 4.297

7.  Variance components estimation for farrowing traits of three purebred pigs in Korea.

Authors:  Bryan Irvine Lopez; Tae Hun Kim; Milton Tinashe Makumbe; Chol Won Song; Kang Seok Seo
Journal:  Asian-Australas J Anim Sci       Date:  2017-03-21       Impact factor: 2.509

8.  Genome-wide association analyses using a Bayesian approach for litter size and piglet mortality in Danish Landrace and Yorkshire pigs.

Authors:  Xiangyu Guo; Guosheng Su; Ole Fredslund Christensen; Luc Janss; Mogens Sandø Lund
Journal:  BMC Genomics       Date:  2016-06-18       Impact factor: 3.969

9.  Genomic BLUP including additive and dominant variation in purebreds and F1 crossbreds, with an application in pigs.

Authors:  Zulma G Vitezica; Luis Varona; Jean-Michel Elsen; Ignacy Misztal; William Herring; Andrès Legarra
Journal:  Genet Sel Evol       Date:  2016-01-29       Impact factor: 4.297

10.  Genomic prediction using models with dominance and imprinting effects for backfat thickness and average daily gain in Danish Duroc pigs.

Authors:  Xiangyu Guo; Ole Fredslund Christensen; Tage Ostersen; Yachun Wang; Mogens Sandø Lund; Guosheng Su
Journal:  Genet Sel Evol       Date:  2016-09-13       Impact factor: 4.297

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