Literature DB >> 24671579

Feed intake, average daily gain, feed efficiency, and real-time ultrasound traits in Duroc pigs: I. Genetic parameter estimation and accuracy of genomic prediction.

S Jiao1, C Maltecca2, K A Gray3, J P Cassady1.   

Abstract

The efficiency of producing salable products in the pork industry is largely determined by costs associated with feed and by the amount and quality of lean meat produced. The objectives of this paper were 1) to explore heritability and genetic correlations for growth, feed efficiency, and real-time ultrasound traits using both pedigree and marker information and 2) to assess accuracy of genomic prediction for those traits using Bayes A prediction models in a Duroc terminal sire population. Body weight at birth (BW at birth) and weaning (BW at weaning) and real-time ultrasound traits, including back fat thickness (BF), muscle depth (MD), and intramuscular fat content (IMF), were collected on the basis of farm protocol. Individual feed intake and serial BW records of 1,563 boars obtained from feed intake recording equipment (FIRE; Osborne Industries Inc., Osborne, KS) were edited to obtain growth, feed intake, and feed efficiency traits, including ADG, ADFI, feed conversion ratio (FCR), and residual feed intake (RFI). Correspondingly, 1,047 boars were genotyped using the Illumina PorcineSNP60 BeadChip. The remaining 516 boars, as an independent sample, were genotyped with a low-density GGP-Porcine BeadChip and imputed to 60K. Magnitudes of heritability from pedigree analysis were moderate for growth, feed intake, and ultrasound traits (ranging from 0.44 ± 0.11 for ADG to 0.58 ± 0.09 for BF); heritability estimates were 0.32 ± 0.09 for FCR but only 0.10 ± 0.05 for RFI. Comparatively, heritability estimates using marker information by Bayes A models were about half of those from pedigree analysis, suggesting "missing heritability." Moderate positive genetic correlations between growth and feed intake (0.32 ± 0.05) and back fat (0.22 ± 0.04), as well as negative genetic correlations between growth and feed efficiency traits (-0.21 ± 0.08, -0.05 ± 0.07), indicate selection solely on growth traits may lead to an undesirable increase in feed intake, back fat, and reduced feed efficiency. Genetic correlations among growth, feed intake, and FCR assessed by a multiple-trait Bayes A model resulted in increased genetic correlation between ADG and ADFI, a negative correlation between ADFI and FCR, and a positive correlation between ADG and FCR. Accuracies of genomic prediction for the traits investigated, ranging from 9.4% for RFI to 36.5% for BF, were reported that might provide new insight into pig breeding and future selection programs using genomic information.

Entities:  

Keywords:  Duroc; genetic parameters; genomic prediction; growth and feed efficiency; ultrasound traits

Mesh:

Year:  2014        PMID: 24671579     DOI: 10.2527/jas.2013-7338

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


  15 in total

1.  Genetic and phenotypic parameters for feed efficiency and component traits in American mink.

Authors:  Pourya Davoudi; Duy Do; Stefanie M Colombo; Bruce Rathgeber; Guoyu Hu; Mehdi Sargolzaei; Zhiquan Wang; Graham Plastow; Younes Miar
Journal:  J Anim Sci       Date:  2022-08-01       Impact factor: 3.338

Review 2.  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

3.  Estimation of direct and maternal genetic parameters for individual birth weight, weaning weight, and probe weight in Yorkshire and Landrace pigs.

Authors:  Kristen Alves; Flavio S Schenkel; Luiz F Brito; Andy Robinson
Journal:  J Anim Sci       Date:  2018-06-29       Impact factor: 3.159

4.  Maternal and direct genetic parameters for tail length, tail lesions, and growth traits in pigs.

Authors:  Sheila Aikins-Wilson; Mehdi Bohlouli; Sven König
Journal:  J Anim Sci       Date:  2021-01-01       Impact factor: 3.159

5.  Genome-wide association study on legendre random regression coefficients for the growth and feed intake trajectory on Duroc Boars.

Authors:  Jeremy T Howard; Shihui Jiao; Francesco Tiezzi; Yijian Huang; Kent A Gray; Christian Maltecca
Journal:  BMC Genet       Date:  2015-05-30       Impact factor: 2.797

6.  Non-invasive methods for the determination of body and carcass composition in livestock: dual-energy X-ray absorptiometry, computed tomography, magnetic resonance imaging and ultrasound: invited review.

Authors:  A M Scholz; L Bünger; J Kongsro; U Baulain; A D Mitchell
Journal:  Animal       Date:  2015-03-06       Impact factor: 3.240

7.  Genotype-by-environment interactions for reproduction, body composition, and growth traits in maternal-line pigs based on single-step genomic reaction norms.

Authors:  Shi-Yi Chen; Pedro H F Freitas; Hinayah R Oliveira; Sirlene F Lázaro; Yi Jian Huang; Jeremy T Howard; Youping Gu; Allan P Schinckel; Luiz F Brito
Journal:  Genet Sel Evol       Date:  2021-06-17       Impact factor: 4.297

8.  Genomic Prediction of Average Daily Gain, Back-Fat Thickness, and Loin Muscle Depth Using Different Genomic Tools in Canadian Swine Populations.

Authors:  Siavash Salek Ardestani; Mohsen Jafarikia; Mehdi Sargolzaei; Brian Sullivan; Younes Miar
Journal:  Front Genet       Date:  2021-06-03       Impact factor: 4.599

9.  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

10.  Effects of correcting missing daily feed intake values on the genetic parameters and estimated breeding values for feeding traits in pigs.

Authors:  Tetsuya Ito; Kazuo Fukawa; Mai Kamikawa; Satoshi Nikaidou; Masaaki Taniguchi; Aisaku Arakawa; Genki Tanaka; Satoshi Mikawa; Tsutomu Furukawa; Kensuke Hirose
Journal:  Anim Sci J       Date:  2017-08-30       Impact factor: 1.749

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.