• Food Science of Animal Resources
• /
• v.36 no.5
• /
• pp.689-696
• /
• 2016

This study was conducted to find pork quality to meet the needs of consumers. Thus, the meat quality and fatty acid composition of longissimus muscles from purebred pigs (Landrace, Yorkshire, and Duroc) and three-way crossbred LYD pigs were compared and evaluated. Chemical compositions of longissimus muscles were significant (p<0.05) different among pigs. Duroc contained significant (p<0.05) higher fat contents than other pigs, whereas significant (p<0.05) higher moisture contents were observed in Landrace, Yorkshire, and LYD pigs compared to those of Duroc pigs. The values of pH_{24 h} and pH_{14 d} were the highest in Landrace pigs. Myoglobin contents of LYD pigs were higher (p<0.05) than those of purebred pigs. Regarding meat color, Duroc and Yorkshire pigs had higher redness values than Landrace and LYD pigs, while Landrace pigs had the lowest (p<0.05) color values among all pigs. There was no significant difference in shear force or water holding capacity (WHC). Duroc pigs maintained the lowest drip loss during 14 d of cold storage. In sensory evaluation, the marbling scores of Duroc pigs were higher (p<0.05) than other pigs. Regarding fatty acid compositions, total USFA, poly-, n-3, and n-6 contents were the highest (p<0.05) in LYD pigs, while total SFA contents were the highest (p<0.05) in Duroc pigs. Based on these results, purebred pigs had superior overall meat quality to crossbred pigs.

• Genomics & Informatics
• /
• v.16 no.3
• /
• pp.59-64
• /
• 2018

Although pork quality traits are important commercially, genome-wide association studies (GWASs) have not well considered Landrace and Yorkshire pigs worldwide. Landrace and Yorkshire pigs are important pork-providing breeds. Although quantitative trait loci of pigs are well-developed, significant genes in GWASs of pigs in Korea must be studied. Through a GWAS using the PLINK program, study of the significant genes in Korean pigs was performed. We conducted a GWAS and surveyed the gene ontology (GO) terms associated with the backfat thickness (BF) trait of these pigs. We included the breed information (Yorkshire and Landrace pigs) as a covariate. The significant genes after false discovery rate (<0.01) correction were AFG1L, SCAI, RIMS1, and SPDEF. The major GO terms for the top 5% of genes were related to neuronal genes, cell morphogenesis and actin cytoskeleton organization. The neuronal genes were previously reported as being associated with backfat thickness. However, the genes in our results were novel, and they included ZNF280D, BAIAP2, LRTM2, GABRA5, PCDH15, HERC1, DTNBP1, SLIT2, TRAPPC9, NGFR, APBB2, RBPJ, and ABL2. These novel genes might have roles in important cellular and physiological functions related to BF accumulation. The genes related to cell morphogenesis were NOX4, MKLN1, ZNF280D, BAIAP2, DNAAF1, LRTM2, PCDH15, NGFR, RBPJ, MYH9, APBB2, DTNBP1, TRIM62, and SLIT2. The genes that belonged to actin cytoskeleton organization were MKLN1, BAIAP2, PCDH15, BCAS3, MYH9, DTNBP1, ABL2, ADD2, and SLIT2.

• Asian-Australasian Journal of Animal Sciences
• /
• v.31 no.12
• /
• pp.1852-1862
• /
• 2018

Objective: The purpose of this study was to investigate a single step genome-wide association study (ssGWAS) for identifying genomic regions affecting reproductive traits in Landrace and Large White pigs. Methods: The traits included the number of pigs weaned per sow per year (PWSY), the number of litters per sow per year (LSY), pigs weaned per litters (PWL), born alive per litters (BAL), non-productive day (NPD) and wean to conception interval per litters (W2CL). A total of 321 animals (140 Landrace and 181 Large White pigs) were genotyped with the Illumina Porcine SNP 60k BeadChip, containing 61,177 single nucleotide polymorphisms (SNPs), while multiple traits single-step genomic BLUP method was used to calculate variances of 5 SNP windows for 11,048 Landrace and 13,985 Large White data records. Results: The outcome of ssGWAS on the reproductive traits identified twenty-five and twenty-two SNPs associated with reproductive traits in Landrace and Large White, respectively. Three known genes were identified to be candidate genes in Landrace pigs including retinol binding protein 7, and ubiquitination factor E4B genes for PWL, BAL, W2CL, and PWSY and one gene, solute carrier organic anion transporter family member 6A1, for LSY and NPD. Meanwhile, five genes were identified to be candidate genes in Large White, two of which, aldehyde dehydrogenase 1 family member A3 and leucine rich repeat kinase 1, associated with all of six reproduction traits and three genes; retrotransposon Gag like 4, transient receptor potential cation channel subfamily C member 5, and LHFPL tetraspan subfamily member 1 for five traits except W2CL. Conclusion: The genomic regions identified in this study provided a start-up point for marker assisted selection and estimating genomic breeding values for improving reproductive traits in commercial pig populations.

• Asian-Australasian Journal of Animal Sciences
• /
• v.31 no.6
• /
• pp.842-850
• /
• 2018

Objective: Several studies have reported the development of new molecular methods for the prognosis and diagnosis of male fertility based on biomarkers aimed at overcoming the limitations of conventional male fertility analysis tools. However, further studies are needed for the field application of these methods. Therefore, alternative methods based on existing semen analysis methods are required to improve production efficiency in the animal industry. Methods: we examined the possibility of improving litter size in various pig breeds using combined Hoechst 33258/chlortetracycline fluorescence (H33258/CTC) staining. The correlation between field fertility and capacitation status by combined H33258/CTC staining in different ejaculates spermatozoa (n = 3) from an individual boar (20 Landrace, 20 Yorkshire, and 20 Duroc) was evaluated as well as overall accuracy. Results: The acrosome reacted (AR) pattern after capacitation (%) was positively correlated with the litter size of Landrace, Yorkshire, and Duroc pigs and the overall accuracy was 75%, 75%, and 70% in Landrace, Yorkshire, and Duroc pigs, respectively. The difference (${\Delta}$) in AR pattern before and after capacitation was positively correlated with the litter size of Landrace, Yorkshire, and Duroc pigs and the overall accuracy was 80%, 65%, and 55% in Landrace, Yorkshire, and Duroc pigs, respectively. However, the difference (${\Delta}$) in capacitated (B) pattern before and after capacitation was negatively correlated with the litter size of Landrace pigs and the overall accuracy was 75%. Moreover, average litter size was significantly altered according to different combined H33258/CTC staining parameters. Conclusion: These results show that combined H33258/CTC staining may be used to predict male fertility in various breeds. However, the selection of specific efficiency combined H33258/CTC staining parameters requires further consideration. Taken together, these findings suggest that combined H33258/CTC staining may constitute an alternative method for predicting male fertility until such time as fertility-related biomarkers are further validated.

• Journal of Animal Science and Technology
• /
• v.47 no.1
• /
• pp.91-98
• /
• 2005

Results of meat quality, physicochemical characteristics, fatty acid and amino acid composition of the Korean Native Black Pig(70 and 90 kg of slaughter weight; KNBP) versus Landrace(110kg of slaughter) are as below. Compared with Landrace, the KNBP exhibited a greater lean meat yield, with no difference in backfat thickness between Landrace and KNBP. There were no difference in chemical composition between Landrace and KNBP, but pH, and cooking loss in the KNBP were superior value than those of the Landrace. These results, KNBP were affected in sensory property and cooking yield. Amino acid content of KNBP and Landrace were significant differences between Landrace and KNBP. Except for the methionine, essential amino acid contents of KNBP had significantly higher than those of Landrace. In the change of fatty acid composition, the Landrace had significantly higher percentages of palmitic(l6: 0), stearic(18: 0) and linolenic(18: 3) acids than that of KNBP, but linoleic acid(l8: 2) was decreased.

• Asian-Australasian Journal of Animal Sciences
• /
• v.15 no.10
• /
• pp.1489-1495
• /
• 2002

Five regions and 258 pigs were selected for this study: North (Beijing), Central (Wuhan), South (Guangzhou), Southwest (Chongqing), Northeast (Harbin). Five typical genetics of growing-finishing pig were selected: Landrace${\times}$Large White${\times}$Beijing Black, Duroc${\times}$Landrace${\times}$Large White, Duroc${\times}$Large White${\times}$Landrace, Landrace${\times}$Rongchang, Landrace${\times}$Harbin White, respectively at each sites. The basal diet was a corn-soybean meal containing sufficient nutrients to meet requirements. Carcass fat-free lean gain was determined by dissecting and analyzing chemical composition of the carcass. Cubic function fitted lean moistures to live weights better than other functions. Exponential function fitted lean lipids to live weights equally to allometric function. Carcass fat-free lean gain of Duroc${\times}$Large White${\times}$Landrace, Landrace${\times}$Large White${\times}$Beijing Black, Duroc${\times}$Landrace${\times}$Large White, Landrace${\times}$Harbin White, Landrace${\times}$Rongchang from 20 to 100 kg of average body weight was 259 g/d, 261 g/d, 311 g/d, 220 g/d, 200 g/d, respectively. All are lower than intermediate fat-free lean gain in NRC (1998).

• Genes and Genomics
• /
• v.40 no.12
• /
• pp.1331-1338
• /
• 2018

Although there have been plenty of dominance deviation analysis, few studies have dealt with multiple phenotypes. Because researchers focused on multiple phenotypes (final weight and backfat thickness) of Landrace pigs, the classification of the genes was possible. With genome-wide association studies (GWASs), we analyzed the additive and dominance effects of the single nucleotide polymorphisms (SNPs). The classification of the pig genes into four categories (overdominance in final weight, overdominance in backfat thickness and overdominance in final weight, underdominance in backfat thickness, etc.) can enable us not only to analyze each phenotype's dominant effects, but also to illustrate the gene ontology (GO) analysis with different aspects. We aimed to determine the additive and dominant effect in backfat thickness and final weight and performed GO analysis. Using additive model and dominance deviation analysis in GWASs, Landrace pigs' overdominant and underdominant SNP effects in final weight and backfat thickness were surveyed. Then through GO analysis, we investigated the genes that were classified in the GWASs. The major GO terms of the underdominant effects in final weight and overdominant effects in backfat thickness were ion transport with the SLC8A3, KCNJ16, P2RX7 and TRPC3 genes. Interestingly, the major GO terms in the underdominant effects in the final weight and the underdominant effects in the backfat thickness were the regulation of ion transport with the STAC, GCK, TRPC6, UBASH3B, CAMK2D, CACNG4 and SCN4B genes. These results demonstrate that ion transport and ion transport regulation genes have distinct dominant effects. Through GWASs using the mode of linear additive model and dominance deviation, overdominant effects and underdominant effects in backfat thickness was contrary to each other in GO terms (ion transport and ion transport regulation, respectively). Additionally, because ion transport and ion transport regulation genes are associative with adipose tissue accumulation, we could infer that these two groups of genes had to do with unique fat accumulation mechanisms in Landrace pigs.

• Animal Bioscience
• /
• v.34 no.12
• /
• pp.1903-1911
• /
• 2021

Objective: The objective of this study was to estimate the genetic parameters and various litter trait trends of Danish pigs in South Vietnam, including the number born alive (NBA), number weaned (NW), and litter weight at the 21st day (LW21). Methods: Records of 936 Yorkshire sows with 3361 litters and 973 Landrace sows with 3161 litters were used to estimate the variance components, genetic parameters, and trends of NBA, NW, and LW21. The restricted maximum likelihood method was applied using VCE6 software to obtain the variance components and genetic parameters. Thereafter, the best linear unbiased prediction procedure with an animal model was applied using PEST software to estimate the breeding values of the studied traits. Results: The heritability estimates were low, ranging from 0.12 to 0.21 for NBA, 0.03 to 0.04 for NW, and from 0.11 to 0.13 for LW21. The genetic correlation between the NBA and NW was relatively strong in both breeds, at 0.77 and 0.60 for Yorkshire and Landrace, respectively. Similarly, the genetic correlation between the NW and LW21 was considerably stronger in Landrace pigs (0.71) than in Yorkshire pigs (0.48). The estimates of annual genetic progress were 0.0431, 0.0233, and 0.0461 for NBA, NW, and LW21 in Landrace pigs and 0434, 0.0202, and 0.0667 for NBA, NW, and LW21 in Yorkshire pigs, respectively. Conclusion: The positive genetic trends estimated for the additive genetic values of the selected traits indicated that the current breeding system has achieved favorable results.

• Asian-Australasian Journal of Animal Sciences
• /
• v.31 no.12
• /
• pp.1980-1990
• /
• 2018

Objective: The aim of this study was to discover the functional impact of non-synonymous single nucleotide polymorphisms (nsSNPs) that were found in selective sweep regions of the Landrace genome Methods: Whole-genome re-sequencing data were obtained from 40 pigs, including 14 Landrace, 16 Yorkshire, and 10 wild boars, which were generated with the Illumina HiSeq 2000 platform. The nsSNPs in the selective sweep regions of the Landrace genome were identified, and the impacts of these variations on protein function were predicted to reveal their potential association with traits of the Landrace breed, such as reproductive capacity. Results: Total of 53,998 nsSNPs in the mapped regions of pigs were identified, and among them, 345 nsSNPs were found in the selective sweep regions of the Landrace genome which were reported previously. The genes featuring these nsSNPs fell into various functional categories, such as reproductive capacity or growth and development during the perinatal period. The impacts of amino acid sequence changes by nsSNPs on protein function were predicted using two in silico SNP prediction algorithms, i.e., sorting intolerant from tolerant and polymorphism phenotyping v2, to reveal their potential roles in biological processes that might be associated with the reproductive capacity of the Landrace breed. Conclusion: The findings elucidated the domestication history of the Landrace breed and illustrated how Landrace domestication led to patterns of genetic variation related to superior reproductive capacity. Our novel findings will help understand the process of Landrace domestication at the genome level and provide SNPs that are informative for breeding.

• Asian-Australasian Journal of Animal Sciences
• /
• v.30 no.2
• /
• pp.149-153
• /
• 2017

Objective: This study was to determine the relationship between estimated breeding value and phenotype information after farrowing when juvenile selection was made in candidate pigs without phenotype information. Methods: After collecting phenotypic and genomic information for the total number of piglets born by Landrace pigs, selection accuracy between genomic breeding value estimates using genomic information and breeding value estimates of best linear unbiased prediction (BLUP) using conventional pedigree information were compared. Results: Genetic standard deviation (${\sigma}_a$) for the total number of piglets born was 0.91. Since the total number of piglets born for candidate pigs was unknown, the accuracy of the breeding value estimated from pedigree information was 0.080. When genomic information was used, the accuracy of the breeding value was 0.216. Assuming that the replacement rate of sows per year is 100% and generation interval is 1 year, genetic gain per year is 0.346 head when genomic information is used. It is 0.128 when BLUP is used. Conclusion: Genetic gain estimated from single step best linear unbiased prediction (ssBLUP) method is by 2.7 times higher than that the one estimated from BLUP method, i.e., 270% more improvement in efficiency.