Digestive efficiency traits in growing pigs are genetically correlated with sow litter traits in the Large White breed

Bouquet, Alban; Déru, Vanille; Blanchet, B.; Ganier, Patrice; Flatres-Grall, Loïc; Ligonesche, Bruno; Carillier-Jacquin, Céline; Labussière, Étienne; Gilbert, Hélène

doi:10.1016/j.animal.2021.100447

Cited by 5 publications

(4 citation statements)

References 14 publications

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“…The same gene with two SNPs in the intron region was also identified by Yuan et al (2012) in sheep in addition to observations in cattle (Chen et al, 2018). IGF1 gene polymorphisms have been reported consistently in three studies (Grochowska et al, 2021;Li et al, 2021;Meira et al, 2019) in concordance with reports in other species such as cattle (Yang, Zhu, et al, 2022), pigs (Bouquet et al, 2021), and fish (Chandhini et al, 2021) suggesting IGF1 to be a possible marker of growth and FE. Polymorphisms in the intron region of IGF1 was found to be associated with carcass traits such as length of carcass and rib yield (Meira et al, 2019).…”

Section: Other Putative Omics Markers Of Fe Carcass and Meat Quality ...supporting

confidence: 78%

Insights into the influence of diet and genetics on feed efficiency and meat production in sheep

Chacko Kaitholil,

Mooney,

Aubry

et al. 2023

Animal Genetics

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Feed costs and carcass yields affect the profitability and sustainability of sheep production. Therefore, it is crucial to select animals with a higher feed efficiency and high‐quality meat production. This study focuses on the impact of dietary and genetic factors on production traits such as feed efficiency, carcass quality, and meat quality. Diets promote optimal sheep growth and development and provide sufficient protein can lead to higher‐quality meat. However, establishing an optimized production system requires careful consideration and balance of dietary parameters. This includes ensuring adequate protein intake and feeding diets with higher intestinal absorption rates to enhance nutrient absorption in the gut. The study identifies specific genes, such as Callipyge, Calpastatin, and Myostatin, and the presence of causal mutations in these genes, as factors influencing animal growth rates, feed efficiency, and meat fatty acid profiles. Additionally, variants of other reported genes, including PIGY, UCP1, MEF2B, TNNC2, FABP4, SCD, FASN, ADCY8, ME1, CA1, GLIS1, IL1RAPL1, SOX5, SOX6, and IGF1, show potential as markers for sheep selection. A meta‐analysis of reported heritability estimates reveals that residual feed intake (0.27 ± 0.07), hot carcass weight (0.26 ± 0.05), dressing percentage (0.23 ± 0.05), and intramuscular fat content (0.45 ± 0.04) are moderately to highly heritable traits. This suggests that these traits are less influenced by environmental factors and could be improved through genetic selection. Additionally, positive genetic correlations exist between body weight and hot carcass weight (0.91 ± 0.06), dressing percentage (0.35 ± 0.15), and shear force (0.27 ± 0.24), indicating that selecting for higher body weight could lead to favorable changes in carcass quality, and meat quality.

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Section: Other Putative Omics Markers Of Fe Carcass and Meat Quality ...supporting

confidence: 78%

Insights into the influence of diet and genetics on feed efficiency and meat production in sheep

Chacko Kaitholil,

Mooney,

Aubry

et al. 2023

Animal Genetics

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“…Ito et al (2018) estimated a positive genetic correlation between ADG and average feed intake from 30 to 100 kg in Duroc pigs, although they did not discuss the association between ADG and total feed intake. Previous studies investigated the genetic association between feed efficiency and litter performance traits in populations outside Japan (e.g., Bouquet et al, 2022; Estany et al, 2002; Gilbert et al, 2012). Further studies would be valuable to assess genetic correlations with economically important traits that were not included in this study.…”

Section: Resultsmentioning

confidence: 99%

“…To the best of our knowledge, no study has reported results for Large White pigs. In foreign populations, many studies have estimated genetic correlations of NBA with days to reach a particular body weight, ADG, and BF for different breeds (e.g., Banville et al, 2014; Lopez et al, 2018; Wolf et al, 2005), while those reporting estimated genetic correlations between pork production and litter performance at weaning were limited (e.g., Aikins‐Wilson et al, 2021; Banville et al, 2014; Bouquet et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Genetic parameter estimation for pork production and litter performance traits of Landrace, Large White, and Duroc pigs in Japan

Ogawa

Takahashi²,

Satoh

2023

J Animal Breeding Genetics

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We estimated genetic parameters for two pork production and six litter performance traits of Landrace, Large White, and Duroc pigs reared in Japan. Pork production traits were average daily gain from birth to end of performance testing and backfat thickness at end of testing (46,042 records for Landrace, 40,467 records for Large White, and 42,920 records for Duroc). Litter performance traits were number born alive, litter size at weaning (LSW), number of piglets dead during suckling (ND), survival rate of piglets during suckling (SV), total piglet weight at weaning (TWW), and average piglet weight at weaning (AWW) (27,410, 26,716, and 12,430 records for Landrace, Large White, and Duroc, respectively). ND was calculated as the difference between LSW and litter size at start of suckling (LSS). SV was calculated as LSW/LSS. AWW was calculated as TWW/LSW. Pedigree data for Landrace, Large White, and Duroc breeds contained 50,193, 44,077, and 45,336 pigs, respectively. Trait heritability was estimated via single‐trait analysis and genetic correlation between two traits was estimated via two‐trait analysis. When considering the linear covariate of LSS in the statistical model for LSW and TWW, for all breeds, the heritability was estimated to be 0.4–0.5 for pork production traits and below 0.2 for litter performance traits. Estimated genetic correlation between average daily gain and backfat thickness was small, ranging from 0.057 to 0.112, and those between pork production traits and litter performance traits were negligible to moderate, ranging from −0.493 to 0.487. A wide range of genetic correlation values among the litter performance traits was estimated, while that between LSW and ND could not be obtained. The results of genetic parameter estimation were affected by whether the linear covariate of LSS was included in the statistical model for LSW and TWW or not. This finding implies the necessity of carefully interpreting the results according to the choice of statistical model. Our results could give fundamental information on simultaneously improving productivity and female reproductivity for pigs.

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“…In addition, another study used heterogeneous residuals in their model. Bouquet et al (2022) used Levene's test to test the homogeneity residual of all traits. Their heterogeneous residual analysis included the environmental effects of different diets on those traits, such as daily feed intake, feed conversion ratio, and digestibility coefficients of nitrogen.…”

Section: Discussionmentioning

confidence: 99%

Does the climate influence the variance of residual in litter traits of Taiwan Landrace sows?

Lin

2023

Can. J. Anim. Sci.

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Heat stress adversely affects the litter traits of Landrace, the primary dam breed in Taiwan. This study aimed to evaluate the effects of heat stress during sow pregnancy with homogeneous and heterogeneous residuals to estimate the genetic parameters of the Taiwan Landrace. Performance records for 11,657 litters and weather data from 2008 to 2021 were collected. The climate effect was defined proportionally from cool to hot for climates 1 to 5. The homogeneous residual analysis showed that the heritabilities of the total number born (TNB) and number born alive (NBA) were 0.164 ± 0.014 and 0.111 ± 0.014 with residual variances of 10.338 and 9.164, respectively. The heterogeneous residual analysis showed that, the residual variances for TNB and NBA were 8.934-11.113 and 8.196-9.810, respectively. For TNB, the residual variance in the Herd-Year-Climate effect differed significantly in climate 1 from climates 3 to 5 (p < 0.01). In NBA, the residual variance was significantly lower in climates 1 and 2 than in climates 3 and 5 (p < 0.01). In conclusion, heritability was estimated for TNB and NBA. In addition, residual variances could interact with the climate effect in heterogeneous residual analysis.

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Digestive efficiency traits in growing pigs are genetically correlated with sow litter traits in the Large White breed

Cited by 5 publications

References 14 publications

Insights into the influence of diet and genetics on feed efficiency and meat production in sheep

Insights into the influence of diet and genetics on feed efficiency and meat production in sheep

Genetic parameter estimation for pork production and litter performance traits of Landrace, Large White, and Duroc pigs in Japan

Does the climate influence the variance of residual in litter traits of Taiwan Landrace sows?

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