Literature DB >> 29378008

Genetic correlations between feed efficiency traits, and growth performance and carcass traits in purebred and crossbred pigs.

R M Godinho1,2, R Bergsma3, F F Silva1, C A Sevillano2,3, E F Knol3, M S Lopes3,4, P S Lopes1, J W M Bastiaansen2, S E F Guimarães1.   

Abstract

Selection for feed efficiency (FE) is a strategy to reduce the production costs per unit of animal product, which is one of the major objectives of current animal breeding programs. In pig breeding, selection for FE and other traits traditionally takes place based on purebred pig (PB) performance at the nucleus level, while pork production typically makes use of crossbred animals (CB). The success of this selection, therefore, depends on the genetic correlation between the performance of PB and CB (rpc) and on the genetic correlation (rg) between FE and the other traits that are currently under selection. Different traits are being used to account for FE, but the rpc has been reported only for feed conversion rate. Therefore, this study aimed 1) to estimate the rpc for growth performance, carcass, and FE traits; 2) to estimate rg between traits within PB and CB populations; and 3) to compare three different traits representing FE: feed conversion rate, residual energy intake (REI), and residual feed intake (RFI). Phenotypes of 194,445 PB animals from 23 nucleus farms, and 46,328 CB animals from three farms where research is conducted under near commercial production conditions were available for this study. From these, 22,984 PB and 8,657 CB presented records for feed intake. The PB population consisted of five sire and four dam lines, and the CB population consisted of terminal cross-progeny generated by crossing sires from one of the five PB sire lines with commercially available two-way maternal sow crosses. Estimates of rpc ranged from 0.61 to 0.71 for growth performance traits, from 0.75 to 0.82 for carcass traits, and from 0.62 to 0.67 for FE traits. Estimates of rg between growth performance, carcass, and FE traits differed within PB and CB. REI and RFI showed substantial positive rg estimates in PB (0.84) and CB (0.90) populations. The magnitudes of rpc estimates indicate that genetic progress is being realized in CB at the production level from selection on PB performance at nucleus level. However, including CB phenotypes recorded on production farms, when predicting breeding values, has the potential to increase genetic progress for these traits in CB. Given the genetic correlations with growth performance traits and the genetic correlation between the performance of PB and CB, REI is an attractive FE parameter for a breeding program.

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Year:  2018        PMID: 29378008      PMCID: PMC6093586          DOI: 10.1093/jas/skx011

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


  11 in total

1.  Genetic correlations between two strains of Durocs and crossbreds from differing production environments for slaughter traits.

Authors:  B Zumbach; I Misztal; S Tsuruta; J Holl; W Herring; T Long
Journal:  J Anim Sci       Date:  2006-12-18       Impact factor: 3.159

2.  Multilevel selection 2: Estimating the genetic parameters determining inheritance and response to selection.

Authors:  Piter Bijma; William M Muir; Esther D Ellen; Jason B Wolf; Johan A M Van Arendonk
Journal:  Genetics       Date:  2006-11-16       Impact factor: 4.562

3.  Difference in energy metabolism and protein retention of limit-fed growing pigs of several breeds.

Authors:  A M Henken; W van der Hel; H A Brandsma; M W Verstegen
Journal:  J Anim Sci       Date:  1991-04       Impact factor: 3.159

4.  Selection response and genetic parameters for residual feed intake in Yorkshire swine.

Authors:  W Cai; D S Casey; J C M Dekkers
Journal:  J Anim Sci       Date:  2007-11-12       Impact factor: 3.159

5.  Effects of ad libitum and restricted feeding on early production performance and body composition of Yorkshire pigs selected for reduced residual feed intake.

Authors:  N Boddicker; N K Gabler; M E Spurlock; D Nettleton; J C M Dekkers
Journal:  Animal       Date:  2011-08       Impact factor: 3.240

6.  The relationship between different measures of feed efficiency and feeding behavior traits in Duroc pigs.

Authors:  D Lu; S Jiao; F Tiezzi; M Knauer; Y Huang; K A Gray; C Maltecca
Journal:  J Anim Sci       Date:  2017-08       Impact factor: 3.159

7.  Genetic and statistical properties of residual feed intake.

Authors:  B W Kennedy; J H van der Werf; T H Meuwissen
Journal:  J Anim Sci       Date:  1993-12       Impact factor: 3.159

8.  Genetic correlations between lactation performance and growing-finishing traits in pigs.

Authors:  R Bergsma; P K Mathur; E Kanis; M W A Verstegen; E F Knol; J A M Van Arendonk
Journal:  J Anim Sci       Date:  2013-07-23       Impact factor: 3.159

9.  Pedigree and genomic evaluation of pigs using a terminal-cross model.

Authors:  Llibertat Tusell; Hélène Gilbert; Juliette Riquet; Marie-José Mercat; Andres Legarra; Catherine Larzul
Journal:  Genet Sel Evol       Date:  2016-04-07       Impact factor: 4.297

Review 10.  Review: divergent selection for residual feed intake in the growing pig.

Authors:  H Gilbert; Y Billon; L Brossard; J Faure; P Gatellier; F Gondret; E Labussière; B Lebret; L Lefaucheur; N Le Floch; I Louveau; E Merlot; M-C Meunier-Salaün; L Montagne; P Mormede; D Renaudeau; J Riquet; C Rogel-Gaillard; J van Milgen; A Vincent; J Noblet
Journal:  Animal       Date:  2017-01-25       Impact factor: 3.240

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  12 in total

1.  Genome-wide association study for carcass quality traits and growth in purebred and crossbred pigs1.

Authors:  Matteo Bergamaschi; Christian Maltecca; Justin Fix; Clint Schwab; Francesco Tiezzi
Journal:  J Anim Sci       Date:  2020-01-01       Impact factor: 3.159

2.  A Genome-Wide Association Study on Feed Efficiency Related Traits in Landrace Pigs.

Authors:  Lu Fu; Yao Jiang; Chonglong Wang; Mengran Mei; Ziwen Zhou; Yifan Jiang; Hailiang Song; Xiangdong Ding
Journal:  Front Genet       Date:  2020-07-03       Impact factor: 4.599

Review 3.  Application of Genetic, Genomic and Biological Pathways in Improvement of Swine Feed Efficiency.

Authors:  Pourya Davoudi; Duy Ngoc Do; Stefanie M Colombo; Bruce Rathgeber; Younes Miar
Journal:  Front Genet       Date:  2022-06-09       Impact factor: 4.772

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.  Comparison of cecal microbiota composition in hybrid pigs from two separate three-way crosses.

Authors:  Yuting Yang; Liyan Shen; Huan Gao; Jinming Ran; Xian Li; Hengxin Jiang; Xueyan Li; Zhenhui Cao; Ying Huang; Sumei Zhao; Chunlian Song; Hongbin Pan
Journal:  Anim Biosci       Date:  2020-12-01

6.  Meta-analysis of genome-wide association studies for loin muscle area and loin muscle depth in two Duroc pig populations.

Authors:  Zhanwei Zhuang; Shaoyun Li; Rongrong Ding; Ming Yang; Enqin Zheng; Huaqiang Yang; Ting Gu; Zheng Xu; Gengyuan Cai; Zhenfang Wu; Jie Yang
Journal:  PLoS One       Date:  2019-06-12       Impact factor: 3.240

7.  Optimizing design to estimate genetic correlations between environments with common environmental effects.

Authors:  Maria Lozano-Jaramillo; Hans Komen; Yvonne C J Wientjes; Han A Mulder; John W M Bastiaansen
Journal:  J Anim Sci       Date:  2020-02-01       Impact factor: 3.159

8.  Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin.

Authors:  Claudia A Sevillano; Jan Ten Napel; Simone E F Guimarães; Fabyano F Silva; Mario P L Calus
Journal:  BMC Genomics       Date:  2018-10-11       Impact factor: 3.969

9.  Effects of sire line, birth weight and sex on growth performance and carcass traits of crossbred pigs under standardized environmental conditions.

Authors:  Kathrin Elbert; Neal Matthews; Ralf Wassmuth; Jens Tetens
Journal:  Arch Anim Breed       Date:  2020-11-03

Review 10.  Why breed disease-resilient livestock, and how?

Authors:  Pieter W Knap; Andrea Doeschl-Wilson
Journal:  Genet Sel Evol       Date:  2020-10-14       Impact factor: 4.297

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