Index selection for improved growth and carcass characteristics in a population of Large White pigs

Ellis, Michael; Chadwick, J. P.; Smith, W. C.; Laird, R.

doi:10.1017/s0003356100042331

Cited by 10 publications

(2 citation statements)

References 18 publications

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“…Reduced daily food intake was reported by McPhee (1981) and Ellis et al (1988) with selection for lean efficiency, which was similar to the present study. However, responses in daily food intake to selection for lean growth rate were population dependent in the present study, and the responses of Vangen (1979 and1980) and Sather and Fredeen (1978) were also seemingly conflicting.…”

Section: Discussionsupporting

confidence: 92%

Selection for components of efficient lean growth rate in pigs 4. Genetic and phenotypic parameter estimates and correlated responses in performance test traits with ad-libitum feeding

Cameron

Curran

1994

Anim. Sci.

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Genetic and phenotypic parameters and correlated responses in performance test traits were estimated for populations of Large White (LW) and British Landrace (LR) pigs tested in Edinburgh andWye respectively, to four generations of divergent selection for lean growth rate (LGA), lean food conversion (LFC) and daily food intake (DFI) with ad-libitum feeding. There were differences between the two populations in genetic parameters, as LW heritabilities for growth rate, daily food intake and backfat depths were higher and the correlation between growth rate and backfat was positive for LW, but negative for LR. However, heritabilities, genetic and phenotypic correlations were generally comparable between selection groups, within each population. Genetic and phenotypic correlations indicated that animals with high daily food intakes were faster growing, had positive residual food intakes (RFI), were fatter with higher food conversion ratios. RFI was highly correlated with daily food intake and food conversion ratio, but phenotypically independent of growth rate and backfat, as expected. Selection for LGA, in LW and LR populations, increased growth rate (54 and 101 g/day), but reduced backfat (-3-9 and -2-0 mm), food conversion ratio (-0-23 and -0-25) and total food intake (-11-8 and -12-6 kg). There was no change in daily food intake in LW pigs (-19 g/day), but daily food intake increased in the LR pigs (69 g/day). With selection for LFC in LW and LR populations, there was no response in groivth rate (9 and 9 g/day), but backfat (-4-1 and -2-1 mm), total (-6-6 and -11-8 kg) and daily food intake (-90 and -172 g) were reduced, as animals had lower food conversion ratios (-0-13 and -0-22). LW and LR pigs selected for DFI ate more food in total (6-8 and 5-9 kg) and on a daily basis (314 and 230 g), grew faster (94 and 51 g/day) and had higher food conversion ratios (0-12 and 0-13). Backfat was increased in LW pigs (3-7 mm), but not in the LR population. In general, efficiency of lean growth was improved by increasing groivth rate, with little change in daily food intake from selection for LGA, but was primarily due to reduced daily food intake with selection on LFC.

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Section: Discussionsupporting

confidence: 92%

Selection for components of efficient lean growth rate in pigs 4. Genetic and phenotypic parameter estimates and correlated responses in performance test traits with ad-libitum feeding

Cameron

Curran

1994

Anim. Sci.

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“…Economically relevant traits that are utilized in selection indices are generally quantitative in nature; thus, these traits are controlled by large numbers of causal variants, termed quantitative trait loci (QTL) first by Geldermann [7,8] in 1975. Artificial selection using selection indices in pig breeding programs has been proven to cause significant changes to the mean phenotype of any one trait considered within the breeding objective [9][10][11]. However, artificial selection pressure, especially over relatively short time scales, causes only subtle changes to allele frequencies at QTLs across the genome [12,13].…”

Section: Introductionmentioning

confidence: 99%

Analysis of polygenic selection in purebred and crossbred pig genomes using Generation Proxy Selection Mapping

Grohmann

Shull²,

Crum³

et al. 2022

Preprint

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Background Artificial selection on quantitative traits using breeding values and selection indices in commercial livestock breeding populations causes changes in allele frequency over time, termed polygenic selection, at causal loci and the surrounding genomic regions. Researchers and managers of pig breeding programs are motivated to understand the genetic basis of phenotypic diversity across genetic lines, breeds, and populations using selection mapping analyses. Here, we applied Generation Proxy Selection Mapping (GPSM), a genome-wide association analysis of SNP genotype (38,294 to 46,458 SNPs) of birth date, in four pig populations (15,457, 15,772, 16,595 and 8,447 pigs per population) to identify loci responding to artificial selection over a span of five to ten years. Gene-drop simulation analyses were conducted to validate GPSM results. Selection signatures within and across each population of pigs were compared in the context of commercial pork production. Results Forty-nine to 854 loci were identified by GPSM as under selection (Q-values less than 0.10) across 15 subsets of pigs based on population combinations. The number of significant associations increased as populations of pigs were pooled. In addition, several significant associations were identified in more than one population. These results indicate concurrent selection objectives, similar genetic architectures, and shared causal variants responding to selection across populations. Negligible error rates (less than or equal to 0.02%) of false-positive associations were identified when testing GPSM on gene-drop simulated genotypes, suggesting that GPSM distinguishes selection from random genetic drift in actual pig populations. Conclusions This work confirms the efficacy and accuracy of the GPSM method in detecting selected loci in commercial pig populations. Our results suggest shared selection objectives and genetic architectures across swine populations. Identified polygenic selection highlights loci important to swine production.

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An approach to prediction of feed intake in growing pigs using simple body measurements

Whittemore

Kerr

Cameron

1995

Agricultural Systems

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Index selection for improved growth and carcass characteristics in a population of Large White pigs

Cited by 10 publications

References 18 publications

Selection for components of efficient lean growth rate in pigs 4. Genetic and phenotypic parameter estimates and correlated responses in performance test traits with ad-libitum feeding

Selection for components of efficient lean growth rate in pigs 4. Genetic and phenotypic parameter estimates and correlated responses in performance test traits with ad-libitum feeding

Analysis of polygenic selection in purebred and crossbred pig genomes using Generation Proxy Selection Mapping

An approach to prediction of feed intake in growing pigs using simple body measurements

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