Genetic parameters for production traits and measures of residual feed intake in large white swine.

Johnson, Z. B.; Chewning, J. J.; Nugent, R. A.

doi:10.2527/1999.7771679x

Cited by 79 publications

(96 citation statements)

References 24 publications

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“…However, these latter authors did not show any effect on feed intake. In our study, QTL effects on ADG were positively correlated with QTL effects on DFI, which agrees with the genetic correlation between these traits (Johnson et al, 1999). This would imply that the alleles increasing ADG would be linked to alleles increasing DFI.…”

Section: Discussionsupporting

confidence: 89%

“…QTL for DFI (Duthie et al, 2008) and for tissue composition of the ham (Heuven et al, 2009) in a commercial cross including the PI breed were detected in this same region. Correlations between the effects of the SSC2 QTL on different traits indicated that haplotypes increasing TFI might be physically linked to haplotypes increasing BFT, in the direction of known genetic correlations (Johnson et al, 1999). On the contrary, their correlations with the QTL effects on LMC showed no clear pattern, suggesting that two different loci could segregate in the region.…”

Section: Discussionmentioning

confidence: 96%

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Detecting QTL for feed intake traits and other performance traits in growing pigs in a Piétrain–Large White backcross

Gilbert

Riquet

Gruand

et al. 2010

Animal

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Knowing the large difference in daily feed intake (DFI) between Large White (LW) and Pié train (PI) growing pigs, a backcross (BC) population has been set up to map QTL that could be used in marker assisted selection strategies. LW 3 PI boars were mated with sows from two LW lines to produce 16 sire families. A total of 717 BC progeny were fed ad libitum from 30 to 108 kg BW using single-place electronic feeders. A genome scan was conducted using genotypes for the halothane gene and 118 microsatellite markers spread on the 18 porcine autosomes. Interval mapping analyses were carried out, assuming different QTL alleles between sire families to account for within breed variability using the QTLMap software. The effects of the halothane genotype and of the dam line on the QTL effect estimates were tested. One QTL for DFI (P , 0.05 at the chromosome-wide (CW) level) and one QTL for feed conversion ratio (P , 0.01 at the CW level) were mapped to chromosomes SSC6 -probably due to the halothane allelesand SSC7, respectively. Three putative QTL for feed intake traits were detected (P , 0.06 at the CW level) on SSC2, SSC7 and SSC9. QTL on feeding traits had effects in the range of 0.20 phenotypic s.d. The relatively low number of QTL detected for these traits suggests a large QTL allele variability within breeds and/or low effects of individual loci. Significant QTL were detected for traits related to carcass composition on chromosomes SSC6, SSC15 and SSC17, and to meat quality on chromosome SSC6 (P , 0.01 at the genome-wide level). QTL effects for body composition on SSC13 and SSC17 differed according to the LW dam line, which confirmed that QTL alleles were segregating in the LW breed. An epistatic effect involving the halothane locus and a QTL for loin weight on SSC7 was identified, the estimated substitution effects for the QTL differing by 200 g between Nn and NN individuals. The interactions between QTL alleles and genetic background or particular genes suggest further work to validate QTL segregations in the populations where marker assisted selection for the QTL would be applied.Keywords: QTL, pig, feed intake, feed efficiency, Pié train 3 Large White ImplicationsFeed efficiency of the growing pig has long been selected, and improved, through indirect selection for faster growth and leaner carcass. Further reduction of body fatness could, however, affect meat quality and reproductive performance. Today, single-place electronic feeders provide accurate measures of individual feed intakes of pigs reared in collective pens. Information is still rather scarce on quantitative trait loci affecting daily feed intake, feed conversion ratio or residual feed intake of growing pigs. This study reports the results of a QTL detection experiment pertaining to feed intake traits and other production traits.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 96%

Detecting QTL for feed intake traits and other performance traits in growing pigs in a Piétrain–Large White backcross

Gilbert

Riquet

Gruand

et al. 2010

Animal

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“…Our estimated ADFI heritability from 1622 individuals was within the range of values being similar to the range of 0.23–0.66 that has previously been reported for swine (Mrode & Kennedy 1993; Johnson et al . 1999; Suzuki et al . 2005; Hoque et al .…”

Section: Discussionmentioning

confidence: 99%

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

Ito

Fukawa

Kamikawa

et al. 2017

Animal Science Journal

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Daily feed intake (DFI) is an important consideration for improving feed efficiency, but measurements using electronic feeder systems contain many missing and incorrect values. Therefore, we evaluated three methods for correcting missing DFI data (quadratic, orthogonal polynomial, and locally weighted (Loess) regression equations) and assessed the effects of these missing values on the genetic parameters and the estimated breeding values (EBV) for feeding traits. DFI records were obtained from 1622 Duroc pigs, comprising 902 individuals without missing DFI and 720 individuals with missing DFI. The Loess equation was the most suitable method for correcting the missing DFI values in 5–50% randomly deleted datasets among the three equations. Both variance components and heritability for the average DFI (ADFI) did not change because of the missing DFI proportion and Loess correction. In terms of rank correlation and information criteria, Loess correction improved the accuracy of EBV for ADFI compared to randomly deleted cases. These findings indicate that the Loess equation is useful for correcting missing DFI values for individual pigs and that the correction of missing DFI values could be effective for the estimation of breeding values and genetic improvement using EBV for feeding traits.

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“…Chen et al (2002) reported estimates of 8 to 12% for backfat across breeds. Crump et al (1997) reported estimates of 5 and 6% in backfat and ADG, respectively, while Johnson et al (1999) reported Table 2 Levels of significance for the fixed factors the analysis of Mukota pigs reared in a common herd †…”

Section: Discussionmentioning

confidence: 99%

Estimation of genetic parameters for growth performance and carcass traits in Mukota pigs

Chimonyo

Dzama

2007

Animal

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The objective of the study was to determine genetic parameters for growth and carcass traits in Mukota pigs, maintained on a fibrous diet. Records (n ¼ 1961) were obtained from a population housed at the University of Zimbabwe Farm (Harare, Zimbabwe) between January 1998 and August 2003. Backfat thickness was measured at 50 and 75 mm (K5 and K7.5), respectively. Carcass length (CL) was measured from the anterior edge of the first rib to the pubic bone using a measuring tape. Variance components were estimated using a model that accounted for direct, common environmental litter and maternal genetic effects, using average information restricted maximum likelihood. Heritability estimates for average daily gain from birth to weaning (ADGW) and average daily gain from weaning to 12 weeks (ADG1) were 0.15 and 0.27, respectively. Maternal genetic effects accounted for 2.6% of variation for ADG1. Heritability for average daily gain from 12 weeks to slaughter (ADG2) was 0.20. Common environmental litter effects accounted for 18% of phenotypic variance for cold dressed mass (CDM). Heritability estimates for CDM and CL were 0.32 and 0.62, respectively. Maternal genetic effects accounted for 10.5% of variance in CL. Heritability estimates for K5 and K7.5 were 0.64 and 0.40, respectively. The CDM was positively genetically correlated to K5, but negative to K7.5. The K5 and K7.5 had a high genetic correlation (0.88). Genetic correlations between ADGW and K5, K7.5 and CL were 0.30, 0.05 and 0.35, respectively. The existence of sufficient genetic variation makes genetic improvement for many growth and carcass traits in the Mukota breed possible through effective selection methods.

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Genetic parameters for production traits and measures of residual feed intake in large white swine.

Cited by 79 publications

References 24 publications

Detecting QTL for feed intake traits and other performance traits in growing pigs in a Piétrain–Large White backcross

Detecting QTL for feed intake traits and other performance traits in growing pigs in a Piétrain–Large White backcross

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

Estimation of genetic parameters for growth performance and carcass traits in Mukota pigs

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