Comparison of genomic predictions for carcass and reproduction traits in Berkshire, Duroc and Yorkshire populations in Korea

Iqbal, Asif; Choi, Tae-Jeong; Kim, You-Sam; Lee, Yun-Mi; Alam, M.; Jung, Jong-Hyun; Choe, Ho-Sung; Kim, Jong-Joo

doi:10.5713/ajas.18.0672

Cited by 4 publications

(5 citation statements)

References 25 publications

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“…The GBLUP model used in the GS analysis demonstrated a prediction accuracy ranging from 0.154 to 0.190. This was not significantly different from the results of genomic prediction accuracy studies on the carcass weight of the pig [26], the carcass traits of sheep [27], and the one-year weight of Hanwoo beef cattle [28]. The findings of this study were reliable.…”

Section: Animals and Datasupporting

confidence: 45%

Genomic Selection for Live Weight in the 14th Month in Alpine Merino Sheep Combining GWAS Information

Li,

Wang

et al. 2023

Animals

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Alpine Merino Sheep is a novel breed reared from Australian Merino Sheep as the father and Gansu Alpine Fine-Wool Sheep as the mother, living all year in cold and arid alpine areas with exceptional wool quality and meat performance. Body weight is an important economic trait of the Alpine Merino Sheep, but there is limited research on identifying the genes associated with live weight in the 14th month for improving the accuracy of the genomic prediction of this trait. Therefore, this study’s sample comprised 1310 Alpine Merino Sheep ewes, and the Fine Wool Sheep 50K Panel was used for genome-wide association study (GWAS) analysis to identify candidate genes. Moreover, the trial population (1310 ewes) in this study was randomly divided into two groups. One group was used as the population for GWAS analysis and screened for the most significant top 5%, top 10%, top 15%, and top 20% SNPs to obtain prior marker information. The other group was used to estimate the genetic parameters based on the weight assigned by heritability combined with different prior marker information. The aim of this study was to compare the accuracy of genomic breeding value estimation when combined with prior marker information from GWAS analysis with the optimal linear unbiased prediction method for genome selection (GBLUP) for the breeding value of target traits. Finally, the accuracy was evaluated using the five-fold cross-validation method. This research provides theoretical and technical support to improve the accuracy of sheep genome selection and better guide breeding. The results demonstrated that eight candidate genes were associated with GWAS analysis, and the gene function query and literature search results suggested that FAM184B, NCAPG, MACF1, ANKRD44, DCAF16, FUK, LCORL, and SYN3 were candidate genes affecting live weight in the 14th month (WT), which regulated the growth of muscle and bone in sheep. In genome selection analysis, the heritability of GBLUP to calculate the WT was 0.335–0.374, the accuracy after five-fold cross-verification was 0.154–0.190, and after assigning different weights to the top 5%, top 10%, top 15%, and top 20% of the GWAS results in accordance with previous information to construct the G matrix, the accuracy of the WT in the GBLUP model was improved by 2.59–7.79%.

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Section: Animals and Datasupporting

confidence: 45%

Genomic Selection for Live Weight in the 14th Month in Alpine Merino Sheep Combining GWAS Information

Li,

Wang

et al. 2023

Animals

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“…An estimate of the correlation of GEBV between traits and ( ) was obtained using the weighted Pearson correlation coefficient of GEBV, as described in [ 43 ]: with and , where and are the GEBV of traits and , respectively, and is the accuracy-based weighting of animal , calculated as . The SE of was derived as where is the number of selected animals that have GEBV accuracies higher than an empirical value of 0.35 [ 44 , 45 ].…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2021

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Background There is an increasing need to account for genotype-by-environment (G × E) interactions in livestock breeding programs to improve productivity and animal welfare across environmental and management conditions. This is even more relevant for pigs because selection occurs in high-health nucleus farms, while commercial pigs are raised in more challenging environments. In this study, we used single-step homoscedastic and heteroscedastic genomic reaction norm models (RNM) to evaluate G × E interactions in Large White pigs, including 8686 genotyped animals, for reproduction (total number of piglets born, TNB; total number of piglets born alive, NBA; total number of piglets weaned, NW), growth (weaning weight, WW; off-test weight, OW), and body composition (ultrasound muscle depth, MD; ultrasound backfat thickness, BF) traits. Genetic parameter estimation and single-step genome-wide association studies (ssGWAS) were performed for each trait. Results The average performance of contemporary groups (CG) was estimated and used as environmental gradient in the reaction norm analyses. We found that the need to consider heterogeneous residual variance in RNM models was trait dependent. Based on estimates of variance components of the RNM slope and of genetic correlations across environmental gradients, G × E interactions clearly existed for TNB and NBA, existed for WW but were of smaller magnitude, and were not detected for NW, OW, MD, and BF. Based on estimates of the genetic variance explained by the markers in sliding genomic windows in ssGWAS, several genomic regions were associated with the RNM slope for TNB, NBA, and WW, indicating specific biological mechanisms underlying environmental sensitivity, and dozens of novel candidate genes were identified. Our results also provided strong evidence that the X chromosome contributed to the intercept and slope of RNM for litter size traits in pigs. Conclusions We provide a comprehensive description of G × E interactions in Large White pigs for economically-relevant traits and identified important genomic regions and candidate genes associated with GxE interactions on several autosomes and the X chromosome. Implementation of these findings will contribute to more accurate genomic estimates of breeding values by considering G × E interactions, in order to genetically improve the environmental robustness of maternal-line pigs.

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“…The estimates of heritability for meat quality and carcass composition traits for 80% of the traits exhibited larger and more accurate values, that is, lower SE, with either G IBS or G IBD than with A 22 . In previous reports from pure and crossbreed pig populations, the estimates of heritabilities for traits of meat quality and carcass composition were in the range of those obtained by us, either by fitting A 22 (Miar et al, 2014;Van Wijk et al, 2005;Willson et al, 2020), or G IBS (Casiró et al, 2017;Iqbal et al, 2019) or using the single-step covariance matrix H (Khanal et al, 2019), whereas there are no studies employing the G IBD covariance structure. More accurate estimates of heritability can be achieved when dense marker information is available, since it should not be subject to pedigree errors (Hayes & Goddard, 2008).…”

Section: Estimation Of Heritabilitymentioning

confidence: 67%

“…In the estimation of

σ_{u}^{2}

between genomic covariance specifications, the

G_{IBD}

model showed a slight increment compared to

G_{IBS}

model for all traits analysed in the current research. Previous studies estimating variance components for meat quality traits in pigs have employed one approach to set up the covariance matrix of BV (i.e., pedigree‐based A , GBLUP G , or Single‐Step H matrices; Iqbal et al, 2019; Khanal et al, 2019; Van Wijk et al, 2005; Willson et al, 2020). Neither research used a

G_{IBD}

relationship matrix, nor a comparison of models has been done.…”

Section: Discussionmentioning

confidence: 99%

Heritability estimates and predictive ability for pig meat quality traits using identity‐by‐state and identity‐by‐descent relationships in an F₂ population

Barajas

Cantet

Steibel

et al. 2022

J Animal Breeding Genetics

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Genomic relationships can be computed with dense genome-wide genotypes through different methods, either based on identity-by-state (IBS) or identityby-descent (IBD). The latter has been shown to increase the accuracy of both estimated relationships and predicted breeding values. However, it is not clear whether an IBD approach would achieve greater heritability (h 2 ) and predictive ability (r y,ŷ ) than its IBS counterpart for data with low-depth pedigrees. Here, we compare both approaches in terms of the estimated of h 2 and ry,ŷ , using data on meat quality and carcass traits recorded in experimental crossbred pigs, with a pedigree constrained to only three generations. Three animal models were fitted which differed on the relationship matrix: an IBS model (G IBS ), an IBD (defined within the known pedigree) model (G IBD ), and a pedigree model (A 22 ). In 9 of 20 traits, the range of increase for the estimates of 2 u and h 2 was 1.2-2.9 times greater with G IBS and G IBD models than with A 22 . Whereas for all traits, both parameters were similar between genomic models. The ry,ŷ of the genomic models was higher compared to A 22 . A scarce increment in ry,ŷ was found with G IBS when compared to G IBD , most likely due to the former recovering sizeable relationships among founder F 0 animals.

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Comparison of genomic predictions for carcass and reproduction traits in Berkshire, Duroc and Yorkshire populations in Korea

Cited by 4 publications

References 25 publications

Genomic Selection for Live Weight in the 14th Month in Alpine Merino Sheep Combining GWAS Information

Genomic Selection for Live Weight in the 14th Month in Alpine Merino Sheep Combining GWAS Information

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

Heritability estimates and predictive ability for pig meat quality traits using identity‐by‐state and identity‐by‐descent relationships in an F₂ population

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Comparison of genomic predictions for carcass and reproduction traits in Berkshire, Duroc and Yorkshire populations in Korea

Cited by 4 publications

References 25 publications

Genomic Selection for Live Weight in the 14th Month in Alpine Merino Sheep Combining GWAS Information

Genomic Selection for Live Weight in the 14th Month in Alpine Merino Sheep Combining GWAS Information

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

Heritability estimates and predictive ability for pig meat quality traits using identity‐by‐state and identity‐by‐descent relationships in an F2 population

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Heritability estimates and predictive ability for pig meat quality traits using identity‐by‐state and identity‐by‐descent relationships in an F₂ population