Genetic parameters and purebred-crossbred genetic correlations for growth, meat quality, and carcass traits in pigs

Additive and Dominance Genome-Wide Association Studies Reveal the Genetic Basis of Heterosis Related to Growth Traits of Duhua Hybrid Pigs

Heterosis has been extensively used for pig genetic breeding and production, but the genetic basis of heterosis remains largely elusive. Crossbreeding between commercial and native breeds provides a good model to parse the genetic basis of heterosis. This study uses Duhua hybrid pigs, a crossbreed of Duroc and Liangguang small spotted pigs, as materials to explore the genetic basis underlying heterosis related to growth traits at the genomic level. The mid-parent heterosis (MPH) analysis showed heterosis of this Duhua offspring on growth traits. In this study, we examined the impact of additive and dominance effects on 100 AGE (age adjusted to 100 kg) and 100 BF (backfat thickness adjusted to 100 kg) of Duhua hybrid pigs. Meanwhile, we successfully identified SNPs associated with growth traits through both additive and dominance GWASs (genome-wide association studies). These findings will facilitate the subsequent in-depth studies of heterosis in the growth traits of Duhua pigs.

Unveiling the Genetic Mechanism of Meat Color in Pigs through GWAS, Multi-Tissue, and Single-Cell Transcriptome Signatures Exploration

Meat color traits directly influence consumer acceptability and purchasing decisions. Nevertheless, there is a paucity of comprehensive investigation into the genetic mechanisms underlying meat color traits in pigs. Utilizing genome-wide association studies (GWAS) on five meat color traits and the detection of selection signatures in pig breeds exhibiting distinct meat color characteristics, we identified a promising candidate SNP, 6_69103754, exhibiting varying allele frequencies among pigs with different meat color characteristics. This SNP has the potential to affect the redness and chroma index values of pork. Moreover, transcriptome-wide association studies (TWAS) analysis revealed the expression of candidate genes associated with meat color traits in specific tissues. Notably, the largest number of candidate genes were observed from transcripts derived from adipose, liver, lung, spleen tissues, and macrophage cell type, indicating their crucial role in meat color development. Several shared genes associated with redness, yellowness, and chroma indices traits were identified, including RINL in adipose tissue, ENSSSCG00000034844 and ITIH1 in liver tissue, TPX2 and MFAP2 in lung tissue, and ZBTB17, FAM131C, KIFC3, NTPCR, and ENGSSSCG00000045605 in spleen tissue. Furthermore, single-cell enrichment analysis revealed a significant association between the immune system and meat color. This finding underscores the significance of the immune system associated with meat color. Overall, our study provides a comprehensive analysis of the genetic mechanisms underlying meat color traits, offering valuable insights for future breeding efforts aimed at improving meat quality.

Comparison on genomic prediction using pedigree BLUP and single step GBLUP through the Hanwoo full-sib family

OBJECTIVE

When evaluating individuals with the same parent and no phenotype by pedigree best linear unbiased prediction (BLUP), it is difficult to explain carcass grade difference and select individuals because they have the same value in pedigree BLUP (PBLUP). However, single step GBLUP (ssGBLUP), which can estimate the breeding value suitable for the individual by adding genotype, is more accurate than the existing method.

METHODS

The breeding value and accuracy were estimated with pedigree BLUP and ssGBLUP using pedigree and genotype of 408 Hanwoo cattle from 16 families with the same parent among siblings produced by fertilized egg transplantation. A total of 14,225 Hanwoo cattle with pedigree, genotype and phenotype were used as the reference population. PBLUP obtained estimated breeding value (EBV) using the pedigree of the test and reference populations, and ssGBLUP obtained genomic EBV (GEBV) after constructing and H-matrix by integrating the pedigree and genotype of the test and reference populations.

RESULTS

For all traits, the accuracy of GEBV using ssGBLUP is 0.18 to 0.20 higher than the accuracy of EBV obtained with PBLUP. Comparison of EBV and GEBV of individuals without phenotype, since the value of EBV is estimated based on expected values of alleles passed down from common ancestors. It does not take Mendelian sampling into consideration, so the EBV of all individuals within the same family is estimated to be the same value. However, GEBV makes estimating true kinship coefficient based on different genotypes of individuals possible, so GEBV that corresponds to each individual is estimated rather than a uniform GEBV for each individual.

CONCLUSION

Since Hanwoo cows bred through embryo transfer have a high possibility of having the same parent, if ssGBLUP after adding genotype is used, estimating true kinship coefficient corresponding to each individual becomes possible, allowing for more accurate estimation of breeding value.

Development and application of an efficient genomic mating method to maximize the production performances of three-way crossbred pigs

Creating synthetic lines is the standard mating mode for commercial pig production. Traditional mating performance was evaluated through a strictly designed cross-combination test at the 'breed level' to maximize the benefits of production. The Duroc-Landrace-Yorkshire (DLY) three-way crossbred production system became the most widely used breeding scheme for pigs. Here, we proposed an 'individual level' genomic mating procedure that can be applied to commercial pig production with efficient algorithms for estimating marker effects and for allocating the appropriate boar-sow pairs, which can be freely accessed to public in our developed HIBLUP software at https://www.hiblup.com/tutorials#genomic-mating. A total of 875 Duroc boars, 350 Landrace-Yorkshire sows and 3573 DLY pigs were used to carry out the genomic mating to assess the production benefits theoretically. The results showed that genomic mating significantly improved the performances of progeny across different traits compared with random mating, such as the feed conversion rate, days from 30 to 120 kg and eye muscle area could be improved by -0.12, -4.64 d and 2.65 cm2, respectively, which were consistent with the real experimental validations. Overall, our findings indicated that genomic mating is an effective strategy to improve the performances of progeny by maximizing their total genetic merit with consideration of both additive and dominant effects. Also, a herd of boars from a richer genetic source will increase the effectiveness of genomic mating further.

Predicting the impact of genotype-by-genotype interaction on the purebred-crossbred genetic correlation from phenotype and genotype marker data of parental lines

BACKGROUND

The genetic correlation between purebred (PB) and crossbred (CB) performances ([Formula: see text]) partially determines the response in CB when selection is on PB performance in the parental lines. An earlier study has derived expressions for an upper and lower bound of [Formula: see text], using the variance components of the parental purebred lines, including e.g. the additive genetic variance in the sire line for the trait expressed in one of the dam lines. How to estimate these variance components is not obvious, because animals from one parental line do not have phenotypes for the trait expressed in the other line. Thus, the aim of this study was to propose and compare three methods for approximating the required variance components. The first two methods are based on (co)variances of genomic estimated breeding values (GEBV) in the line of interest, either accounting for shrinkage (VC_GEBV-S) or not (VC_GEBV). The third method uses restricted maximum likelihood (REML) estimates directly from univariate and bivariate analyses (VC_REML) by ignoring that the variance components should refer to the line of interest, rather than to the line in which the trait is expressed. We validated these methods by comparing the resulting predicted bounds of [Formula: see text] with the [Formula: see text] estimated from PB and CB data for five traits in a three-way cross in pigs.

RESULTS

With both VC_GEBV and VC_REML, the estimated [Formula: see text] (plus or minus one standard error) was between the upper and lower bounds in 14 out of 15 cases. However, the range between the bounds was much smaller with VC_REML (0.15-0.22) than with VC_GEBV (0.44-0.57). With VC_GEBV-S, the estimated [Formula: see text] was between the upper and lower bounds in only six out of 15 cases, with the bounds ranging from 0.21 to 0.44.

CONCLUSIONS

We conclude that using REML estimates of variance components within and between parental lines to predict the bounds of [Formula: see text] resulted in better predictions than methods based on GEBV. Thus, we recommend that the studies that estimate [Formula: see text] with genotype data also report estimated genetic variance components within and between the parental lines.

Genotyping and phenotyping strategies for genetic improvement of meat quality and carcass composition in swine

Background

Meat quality and composition traits have become valuable in modern pork production; however, genetic improvement has been slow due to high phenotyping costs. Combining genomic information with multi-trait indirect selection based on cheaper indicator traits is an alternative for continued cost-effective genetic improvement.

Methods

Data from an ongoing breeding program were used in this study. Phenotypic and genomic information was collected on three-way crossbred and purebred Duroc animals belonging to 28 half-sib families. We applied different methods to assess the value of using purebred and crossbred information (both genomic and phenotypic) to predict expensive-to-record traits measured on crossbred individuals. Estimation of multi-trait variance components set the basis for comparing the different scenarios, together with a fourfold cross-validation approach to validate the phenotyping schemes under four genotyping strategies.

Results

The benefit of including genomic information for multi-trait prediction depended on the breeding goal trait, the indicator traits included, and the source of genomic information. While some traits benefitted significantly from genotyping crossbreds (e.g., loin intramuscular fat content, backfat depth, and belly weight), multi-trait prediction was advantageous for some traits even in the absence of genomic information (e.g., loin muscle weight, subjective color, and subjective firmness).

Conclusions

Our results show the value of using different sources of phenotypic and genomic information. For most of the traits studied, including crossbred genomic information was more beneficial than performing multi-trait prediction. Thus, we recommend including crossbred individuals in the reference population when these are phenotyped for the breeding objective.

Analysis of the use of industrial crossbreeding to improve the profitability of the pig industry

The aim of the research was to conduct an economic assessment of the use of industrial crossbreeding in the pig industry. The study was carried out in LLC "Mayak-Agro" (Ukraine) and in the laboratories of the Cherkasy National University named after Bohdan Khmelnitsky and the Cherkasy Experimental Station of Bioresources of the National Academy of Sciences of Ukraine. Ukrainian breeds of pigs were used: (Ukrainian BigWhite-1 (UBW-1), Red White-Belt (RWB) and Duroc of the Ukrainian selection "Steppe" (DUSS)). Breeds of English origin: (Big White (EBW), Landrace (L), Pietrain (P)). Crossbreeds, obtained by crossing the breeds, mentioned above. A comprehensive assessment of the reproductive capacity of a sow was carried out taking into account multiple births, the number of piglets at one month of age and the average daily gain during this period. Growth and development were monitored in terms of changes in live weight by individual weighing at birth and every month to a live weight of 100 and 120 kg. Regardless of maternal form, in the groups where boars of the breeds Red White-Belt and Pietrain were used, higher indicators of comprehensive assessment of reproductive capacity were obtained. The best fattening qualities characterized piglets, obtained from a combination of sows (1/2UBW-1+1/2L) with boars of the Pietrain breed (P). In comparison with other variants of crosses, in this group the animals reached a live weight of 100 kg 7.6 days earlier. Their feed costs per 1 kg of live weight gain were 3.33 feed units, which corresponds to the expected figure of 3.34 feed units when fattening up to 100 kg in 170 days. In terms of industrial pork production, breeding of animals of the group (1/4UBW-1+1/4L+1/2P) was more profitable, in which the highest level of profitability was obtained - 22.3 % for fattening up to 100 kg and 12.5 % for fattening up to 120 kg. Cultivation of three-breed hybrids to a live weight of over 100 kg led to a decrease in profitability among all research groups. The use of the genotype 1/4UBW-1+1/4L+1/2P in industrial production makes it possible to obtain animals of various weight conditions without significant additional costs and profitability level reduction. In the course of the research, it was found, that the best option for three-breed crossing is the use of boars of the Pietrain and Red White-Belt breeds. The use of boars of these breeds is ideal for producers looking for bacon pork. The use of boars of the Duroc breed of the Ukrainian selection "Steppe" (DUSS) makes it possible to obtain fatty pork with the possibility of fattening to different weight categories.