Development of a method using QuEChERS and LC-MS/MS for analysis of per- and polyfluoroalkyl substances in rice matrix.

Detection of per- and polyfluoroalkyl substances (PFAS) in food is crucial for ensuring food safety. Therefore, we combined a quick, easy, cheap, rugged, and safe (QuEChERS) extraction method with liquid chromatography-triple-quadrupole mass spectrometry (LC-MS/MS) to detect 35 PFAS in rice. The solvents (water and acetonitrile) were adjusted to pH 2.4, a mixture of anhydrous MgSO4, NaCl, and NaOAc was used for extraction, and anhydrous MgSO4, a primary/secondary amine, and graphitized carbon black were applied for purification. The limits of detection and recovery were 0.005-0.100 ng·g-1 and 86.5 %-126.4 %, respectively. When this method was used to detect PFAS in packaged instant rice cooked in a microwave or boiled in water, the microwaved sample showed a lower PFAS content. However, both samples had PFAS contents within WHO guidelines and were safe for consumption. This method can be extended to detect PFAS levels in other foods exposed to packaging materials containing PFAS.

Comparison of accuracy of breeding value for cow from three methods in Hanwoo (Korean cattle) population.

In Korea, Korea Proven Bulls (KPN) program has been well-developed. Breeding and evaluation of cows are also an essential factor to increase earnings and genetic gain. This study aimed to evaluate the accuracy of cow breeding value by using three methods (pedigree index [PI], pedigree-based best linear unbiased prediction [PBLUP], and genomic-BLUP [GBLUP]). The reference population (n = 16,971) was used to estimate breeding values for 481 females as a test population. The accuracy of GBLUP was 0.63, 0.66, 0.62 and 0.63 for carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS), respectively. As for the PBLUP method, accuracy of prediction was 0.43 for CWT, 0.45 for EMA, 0.43 for MS, and 0.44 for BFT. Accuracy of PI method was the lowest (0.28 to 0.29 for carcass traits). The increase by approximate 20% in accuracy of GBLUP method than other methods could be because genomic information may explain Mendelian sampling error that pedigree information cannot detect. Bias can cause reducing accuracy of estimated breeding value (EBV) for selected animals. Regression coefficient between true breeding value (TBV) and GBLUP EBV, PBLUP EBV, and PI EBV were 0.78, 0.625, and 0.35, respectively for CWT. This showed that genomic EBV (GEBV) is less biased than PBLUP and PI EBV in this study. In addition, number of effective chromosome segments (Me) statistic that indicates the independent loci is one of the important factors affecting the accuracy of BLUP. The correlation between Me and the accuracy of GBLUP is related to the genetic relationship between reference and test population. The correlations between Me and accuracy were -0.74 in CWT, -0.75 in EMA, -0.73 in MS, and -0.75 in BF, which were strongly negative. These results proved that the estimation of genetic ability using genomic data is the most effective, and the smaller the Me, the higher the accuracy of EBV.

Inactivation of mammalian spermatozoa on the exposure of TiO2 nanorods deposited with noble metals.

Titanium dioxide (TiO2) nanorods (NRs) are well-known semiconducting and catalytic material that has been widely applied, but their toxicities have also attracted recent interest. In this study, we investigated and compared the toxic effects of TiO2 NRs and TiO2 NRs loaded with Ag or Au NPs on boar spermatozoa. As a result, sperm incubated with Ag-TiO2 NRs showed lower motility than sperm incubated with controls (with or without TiO2 NRs) or Au-TiO2 NRs. In addition, sperm viability and acrosomal integrity were defective in the presence of Ag-TiO2 NRs, and the generation of intracellular reactive oxygen species (ROS) increased significantly when spermatozoa were incubated with 20 µg/ml Ag-TiO2 NRs. We discussed in depth the charge transfer mechanism between enzymatic NADPH and Ag-TiO2 NRs in the context of ROS generation in spermatozoa. The effects we observed reflected the fertilization competence of sperm incubated with Ag-TiO2 NRs; specifically sperm penetration and embryonic development rates by in vitro fertilization were reduced by Ag-TiO2 NRs. To summarize, our findings indicate that exposure to Ag-TiO2 NRs could affect male fertilization fecundity and caution that care be exercised when using these NRs.

Analysis of Vaccenic and Elaidic acid in foods using a silver ion cartridge applied to GC × GC-TOFMS.

Background: Trans fatty acids (TFAs) are unsaturated fatty acids, with vaccenic acid (VA) and elaidic acid (EA) being the major constituents. While VA has been associated with beneficial effects on health and anti-cancer properties, EA is found in hardened vegetable oils and is linked to an increased risk of cardiovascular diseases. Therefore, this study aimed to develop a novel method for the quantitative measurement of VA and EA, aiming to accurately analyze individual TFA and apply it for the assessment of products containing TFAs. Methods: The ratio of VA to EA (V/E ratio) was evaluated using a silver ion cartridge (SIC) solid phase extraction method removing cis-fatty acids (cis-FAs). Additionally, comparative analysis of the V/E ratio was conducted by the two methods (SIC treatment and untreated) using comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC × GC-TOFMS). Results: The removal efficiency of cis-FAs was greater than 97.8%. However, the total TFA contents were not so different from SIC treatment. Moreover, this approach not only allowed for a more precise determination of the V/E ratio but also revealed a significant distinction between natural trans fatty acids (N-TFAs) and hydrogenated trans fatty acids (H-TFAs). Conclusion: Therefore, the SIC coupled to the GC × GC-TOFMS presented in this study could be applied to discriminate N-TFA and H-TFA contents in dairy and fatty foods.

Single nucleotide polymorphism marker combinations for classifying Yeonsan Ogye chicken using a machine learning approach.

Genetic analysis has great potential as a tool to differentiate between different species and breeds of livestock. In this study, the optimal combinations of single nucleotide polymorphism (SNP) markers for discriminating the Yeonsan Ogye chicken (Gallus gallus domesticus) breed were identified using high-density 600K SNP array data. In 3,904 individuals from 198 chicken breeds, SNP markers specific to the target population were discovered through a case-control genome-wide association study (GWAS) and filtered out based on the linkage disequilibrium blocks. Significant SNP markers were selected by feature selection applying two machine learning algorithms: Random Forest (RF) and AdaBoost (AB). Using a machine learning approach, the 38 (RF) and 43 (AB) optimal SNP marker combinations for the Yeonsan Ogye chicken population demonstrated 100% accuracy. Hence, the GWAS and machine learning models used in this study can be efficiently utilized to identify the optimal combination of markers for discriminating target populations using multiple SNP markers.

Time-series transcriptome analysis identified differentially expressed genes in broiler chicken infected with mixed Eimeria species.

Coccidiosis caused by the Eimeria species is a highly problematic disease in the chicken industry. Here, we used RNA sequencing to observe the time-dependent host responses of Eimeria-infected chickens to examine the genes and biological functions associated with immunity to the parasite. Transcriptome analysis was performed at three time points: 4, 7, and 21 days post-infection (dpi). Based on the changes in gene expression patterns, we defined three groups of genes that showed differential expression. This enabled us to capture evidence of endoplasmic reticulum stress at the initial stage of Eimeria infection. Furthermore, we found that innate immune responses against the parasite were activated at the first exposure; they then showed gradual normalization. Although the cytokine-cytokine receptor interaction pathway was significantly operative at 4 dpi, its downregulation led to an anti-inflammatory effect. Additionally, the construction of gene co-expression networks enabled identification of immunoregulation hub genes and critical pattern recognition receptors after Eimeria infection. Our results provide a detailed understanding of the host-pathogen interaction between chicken and Eimeria. The clusters of genes defined in this study can be utilized to improve chickens for coccidiosis control.

Long-term artificial selection of Hanwoo (Korean) cattle left genetic signatures for the breeding traits and has altered the genomic structure.

Indigenous Korean breeds such as Hanwoo (Korean) cattle have adapted to their local environment during the past 5000 years. In the 1980s, the National Genetic Improvement Program was established to develop a modern economic breed for beef production in Korea through artificial selection. This process is thought to have altered the genomic structure of breeding traits over time. The detection of genetic variants under selection could help to elucidate the genetic mechanism of artificial selection in modern cattle breeds. Indigenous Hanwoo cattle have adapted in response to local natural and artificial selection during a 40-year breeding program. We analyzed genomic changes in the selection signatures of an unselected population (USP; n = 362) and a selected population (KPN; n = 667) of Hanwoo cattle. Genomic changes due to long-term artificial selection were identified using a genome-wide integrated haplotype score (iHS) and a genome-wide association study (GWAS). Signatures of recent selection were detected as positive (piHS > 6) or negative (piHS < -6) iHS scores spanning more than 46 related genes in KPN cattle, but none in USP cattle. A region adjacent to the PLAG1 gene was found to be under strong selection for carcass weight. The GWAS results also showed a selection signature on BTA14, but none on BTA13. Pathway and quantitative trait locus analysis results identified candidate genes related to energy metabolism, feed efficiency, and reproductive traits in Hanwoo cattle. Strong selection significantly altered Hanwoo cattle genome structural properties such as linkage disequilibrium (LD) and haplotypes through causal mutation for target traits. Haplotype changes of genome structure which are changes of ancestral allele to derived alleles due to selection were clearly identified on BTA13 and BTA14; however, the structure of the LD block was not clearly observed except BTA14. Thus, selection based on EBVs would be working very well in Hanwoo cattle breeding program appears to have been highly successful.

Identification and quantification of multi-class veterinary drugs and their metabolites in beef using LC-MS/MS.

The practice of abusing antibiotics to improve livestock growth poses a threat to food safety. To prevent and regulate this, accurate monitoring of residual veterinary drugs (VDs) is required. A method based on QuEChERS with dispersive solid-phase extraction for the determination of multi-class VDs was investigated using selected product ions under optimized multiple reaction monitoring conditions. During the clean-up procedure, chitosan, octadecyl silica, primary-secondary amine, and enhanced matrix removal (EMR)-lipid were evaluated for simultaneous analysis of multi-class VDs in beef matrix. The EMR sorbent was most advantageous (113/115) compared to others, and showed a satisfactory recovery range (70.7-117.9%) except cefquinome (67.3%) and cefalonium (69.8%). This methodology can be used to detect oxolinic acid and ractopamine (27.4% and 88.0% of maximum residue limit, respectively) in real beef samples. We thus study propose a simple and fast analytical method for multi-class VDs for the future health of humans and animals.

Serial Improvement of Medial Meniscus Extrusion Following Medial Open-Wedge High Tibial Osteotomy Does Not Correlate With Clinical Outcomes and Arthroscopic Articular Cartilage Improvement.

PURPOSE: To assess serial change up to 2 years in medial meniscus extrusion (MME) following medial open-wedge high tibial osteotomy (MOWHTO) and to determine whether postoperative changes in MME correlated with clinical outcomes and arthroscopic articular cartilage status. METHODS: This study included 26 patients from December 2016 to March 2018 who underwent MOWHTO for primary medial osteoarthritis with varus malalignment. Second-look arthroscopy with plate removal was performed at postoperative 2 years. MME was consecutively measured using coronal magnetic resonance imaging at preoperative and postoperative 3 months, 6 months, 1.5 years, and 2 years. We also assessed which preoperative parameters could reflect the postoperative changes in MME and evaluated whether postoperative clinical outcomes and arthroscopic articular cartilage improvement would be influenced by the MME changes. RESULTS: Regarding the postoperative serial changes in MME values, significant improvement in MME was noted from postoperative 6 months (P = .003), and thereafter, mean MME was further improved with time until postoperative 2 years (P < .001). Regarding the correlation between preoperative parameters and MME changes, preoperative medial proximal tibial angle (MPTA) showed significant correlations in univariate and multivariate analysis (P = .004 and P = .004, respectively). Meanwhile, changes in MME were not correlated with postoperative clinical outcomes or arthroscopic articular cartilage improvement. CONCLUSION: After MOWHTO, MME improved with time and was significantly correlated with preoperative MPTA. However, the changes in MME after MOWHTO did not reflect postoperative clinical and arthroscopic articular cartilage improvement. LEVEL OF EVIDENCE: IV, case series.

Accuracy of genotype imputation based on reference population size and marker density in Hanwoo cattle.

Recently, the cattle genome sequence has been completed, followed by developing a commercial single nucleotide polymorphism (SNP) chip panel in the animal genome industry. In order to increase statistical power for detecting quantitative trait locus (QTL), a number of animals should be genotyped. However, a high-density chip for many animals would be increasing the genotyping cost. Therefore, statistical inference of genotype imputation (low-density chip to high-density) will be useful in the animal industry. The purpose of this study is to investigate the effect of the reference population size and marker density on the imputation accuracy and to suggest the appropriate number of reference population sets for the imputation in Hanwoo cattle. A total of 3,821 Hanwoo cattle were divided into reference and validation populations. The reference sets consisted of 50k (38,916) marker data and different population sizes (500, 1,000, 1,500, 2,000, and 3,600). The validation sets consisted of four validation sets (Total 889) and the different marker density (5k [5,000], 10k [10,000], and 15k [15,000]). The accuracy of imputation was calculated by direct comparison of the true genotype and the imputed genotype. In conclusion, when the lowest marker density (5k) was used in the validation set, according to the reference population size, the imputation accuracy was 0.793 to 0.929. On the other hand, when the highest marker density (15k), according to the reference population size, the imputation accuracy was 0.904 to 0.967. Moreover, the reference population size should be more than 1,000 to obtain at least 88% imputation accuracy in Hanwoo cattle.

A retroviral insertion in the tyrosinase (TYR) gene is associated with the recessive white plumage color in the Yeonsan Ogye chicken.

The recessive white (locus c) phenotype observed in chickens is associated with three alleles (recessive white c, albino ca , and red-eyed white cre ) and causative mutations in the tyrosinase (TYR) gene. The recessive white mutation (c) inhibits the transcription of TYR exon 5 due to a retroviral sequence insertion in intron 4. In this study, we genotyped and sequenced the insertion in TYR intron 4 to identify the mutation causing the unusual white plumage of Yeonsan Ogye chickens, which normally have black plumage. The white chickens had a homozygous recessive white genotype that matched the sequence of the recessive white type, and the inserted sequence exhibited 98% identity with the avian leukosis virus ev-1 sequence. In comparison, brindle and normal chickens had the homozygous color genotype, and their sequences were the same as the wild-type sequence, indicating that this phenotype is derived from other mutation(s). In conclusion, white chickens have a recessive white mutation allele. Since the size of the sample used in this study was limited, further research through securing additional samples to perform validation studies is necessary. Therefore, after validation studies, a selection system for conserving the phenotypic characteristics and genetic diversity of the population could be established if additional studies to elucidate specific phenotype-related genes in Yeonsan Ogye are performed.

Comparison of Selection Signatures between Korean Native and Commercial Chickens Using 600K SNP Array Data.

Korean native chickens (KNCs) comprise an indigenous chicken breed of South Korea that was restored through a government project in the 1990s. The KNC population has not been developed well and has mostly been used to maintain purebred populations in the government research institution. We investigated the genetic features of the KNC population in a selection signal study for the efficient improvement of this breed. We used 600K single nucleotide polymorphism data sampled from 191 KNCs (NG, 38; NL, 29; NR, 52; NW, 39; and NY, 33) and 54 commercial chickens (Hy-line Brown, 10; Lohmann Brown, 10; Arbor Acres, 10; Cobb, 12; and Ross, 12). Haplotype phasing was performed using EAGLE software as the initial step for the primary data analysis. Pre-processed data were analyzed to detect selection signals using the 'rehh' package in R software. A few common signatures of selection were identified in KNCs. Most quantitative trait locus regions identified as candidate regions were associated with traits related to reproductive organs, eggshell characteristics, immunity, and organ development. Block patterns with high linkage disequilibrium values were observed for LPP, IGF11, LMNB2, ERBB4, GABRB2, NTM, APOO, PLOA1, CNTN1, NTSR1, DEF3, CELF1, and MEF2D genes, among regions with confirmed selection signals. NL and NW lines contained a considerable number of selective sweep regions related to broilers and layers, respectively. We recommend focusing on improving the egg and meat traits of KNC NL and NW lines, respectively, while improving multiple traits for the other lines.

Identification of SNPs Associated with Stress Response Traits within High Stress and Low Stress Lines of Japanese Quail.

Mitigation of stress is of great importance in poultry production, as chronic stress can affect the efficiency of production traits. Selective breeding with a focus on stress responses can be used to combat the effects of stress. To better understand the genetic mechanisms driving differences in stress responses of a selectively bred population of Japanese quail, we performed genomic resequencing on 24 birds from High Stress (HS) and Low Stress (LS) lines of Japanese quail using Illumina HiSeq 2 × 150 bp paired end read technology in order to analyze Single Nucleotide Polymorphisms (SNPs) within the genome of each line. SNPs are common mutations that can lead to genotypic and phenotypic variations in animals. Following alignment of the sequencing data to the quail genome, 6,364,907 SNPs were found across both lines of quail. 10,364 of these SNPs occurred in coding regions, from which 2886 unique, non-synonymous SNPs with a SNP% ≥ 0.90 and a read depth ≥ 10 were identified. Using Ingenuity Pathway Analysis, we identified genes affected by SNPs in pathways tied to immune responses, DNA repair, and neurological signaling. Our findings support the idea that the SNPs found within HS and LS lines of quail could direct the observed changes in phenotype.

High Levels of Genetic Variation in MHC-Linked Microsatellite Markers from Native Chicken Breeds.

The major histocompatibility complex (MHC) is a highly polymorphic gene region that regulates cellular communication in all specific immune responses. In this study, we investigated 11 microsatellite (MS) markers in the MHC-B region of chicken populations from four countries: Sri Lanka, Bangladesh, South Korea, and Nigeria. The MS markers were divided into two sets. Set 1 included five novel MS markers, which we assessed using 192 samples from 21 populations. Set 2 included six previously reported markers, which we assessed using 881 samples from 29 populations. The Set 1 MS markers had lower polymorphism (polymorphic information content (PIC) < 0.5) than the Set 2 markers (PIC = 0.4-0.9). In all populations, the LEI0258 marker was the most polymorphic, with a total of 38 alleles (PIC = 0.912, expected heterozygosity (He) = 0.918). Local populations from Sri Lanka, Bangladesh, and Nigeria had higher allele diversity and more haplotypes for Set 2 MS markers than Korean and commercial populations. The Sri Lankan Karuwalagaswewa village population had the highest MHC diversity (mean allele number = 8.17, He = 0.657), whereas the white leghorn population had the lowest (mean allele number = 2.33, He = 0.342). A total of 409 haplotypes (89 shared and 320 unique), with a range of 4 (Rhode Island red) to 46 (Karuwalagaswewa village (TA)), were identified. Among the shared haplotypes, the B21-like haplotype was identified in 15 populations. The genetic relationship observed in a neighbour-joining tree based on the DA distance agreed with the breeding histories and geographic separations. The results indicated high MHC diversity in the local chicken populations. The difference in the allelic pattern among populations presumably reflects the effects of different genotypes, environments, geographic variation, and breeding policies in each country. The selection of MHC allele in domestic poultry can vary due to intensification of poultry production. Preserved MHC diversity in local chicken provides a great opportunity for future studies that address the relationships between MHC polymorphisms and differential immune responses.

Identification of Target Chicken Populations by Machine Learning Models Using the Minimum Number of SNPs.

A marker combination capable of classifying a specific chicken population could improve commercial value by increasing consumer confidence with respect to the origin of the population. This would facilitate the protection of native genetic resources in the market of each country. In this study, a total of 283 samples from 20 lines, which consisted of Korean native chickens, commercial native chickens, and commercial broilers with a layer population, were analyzed to determine the optimal marker combination comprising the minimum number of markers, using a 600 k high-density single nucleotide polymorphism (SNP) array. Machine learning algorithms, a genome-wide association study (GWAS), linkage disequilibrium (LD) analysis, and principal component analysis (PCA) were used to distinguish a target (case) group for comparison with control chicken groups. In the processing of marker selection, a total of 47,303 SNPs were used for classifying chicken populations; 96 LD-pruned SNPs (50 SNPs per LD block) served as the best marker combination for target chicken classification. Moreover, 36, 44, and 8 SNPs were selected as the minimum numbers of markers by the AdaBoost (AB), Random Forest (RF), and Decision Tree (DT) machine learning classification models, which had accuracy rates of 99.6%, 98.0%, and 97.9%, respectively. The selected marker combinations increased the genetic distance and fixation index (Fst) values between the case and control groups, and they reduced the number of genetic components required, confirming that efficient classification of the groups was possible by using a small number of marker sets. In a verification study including additional chicken breeds and samples (12 lines and 182 samples), the accuracy did not significantly change, and the target chicken group could be clearly distinguished from the other populations. The GWAS, PCA, and machine learning algorithms used in this study can be applied efficiently, to determine the optimal marker combination with the minimum number of markers that can distinguish the target population among a large number of SNP markers.

Major histocompatibility complex B variability in Korean native chicken breeds.

Adaptive genetic variations have direct influences on the fitness traits of the animal. The major histocompatibility complex B (MHC-B) region is responsible for adaptive and innate immune responses in chickens. In native Korean chicken breeds, no information on serologically defined B haplotypes is available. We investigated the MHC-B diversity in 5 restored lines of Korean native chicken and Ogye chicken breeds using a recently described MHC-B single-nucleotide polymorphism (SNP) panel and the MHC-linked LEI0258 variable number of tandem repeat marker. High SNP haplotype diversity was observed in Korean native chicken breeds with an average of 9.7 MHC-B SNP haplotypes per line. The total number of haplotypes ranged from 6 to 12 per line, and population-specific haplotypes ranged from 3 to 4. A total of 41 BSNP haplotypes, including 26 novel population-specific haplotypes and 15 common haplotypes, were reported over all populations. The 15 common haplotypes included 7 novel and 8 previously reported standard haplotypes. Selection and breeding evidence supports the observation of common haplotypes between the Korean native chicken and exotic breeds. Similarly, the LEI0258 marker showed allele variation, between 193 bp and 474 bp having 5 to 8 alleles per population. Some of these alleles (193, 249, 309, and 443 bp) were shared and more frequently observed. Comparison between SNP haplotypes and LEI0258 allele sizes for the same samples showed that some LEI0258 allele sizes correspond to more than one BSNP haplotype. The use of the MHC-B SNP panel greatly enhances the identification of MHC diversity compared with the sole use of the LEI0258 marker in native chicken populations.

Genetic diversity and population structure of indigenous chicken of Bangladesh using microsatellite markers.

OBJECTIVE: The objectives of this study were to investigate the genetic diversity, population structure and relatedness among the five chicken populations of Bangladesh using microsatellite markers. METHODS: A total of 161 individuals representing 5 chicken populations (non-descript Deshi [ND], naked neck [NN], hilly [HI], Aseel [AS], and red jungle fowl [JF]) were included in this study to investigate genetic diversity measures, population structure, genetic distance and phylogenetic relationships. Genotyping was performed using 16 selected polymorphic microsatellite markers distributed across 10 chromosomes. RESULTS: The average observed and expected heterozygosity, mean number of alleles and polymorphic information content were found to be 0.67±0.01, 0.70±0.01, 10.7 and 0.748, respectively in the studied populations. The estimated overall fixation index across the loci (F), heterozygote deficiency within (FIS) and among (FIT) chicken populations were 0.04±0.02, 0.05 and 0.16, respectively. Analysis of molecular variance analysis revealed 88.07% of the total genetic diversity was accounted for within population variation and the rest 11.93% was incurred with population differentiation (FST). The highest pairwise genetic distance (0.154) was found between ND and AS while the lowest distance was between JF and AS (0.084). Structure analysis depicted that the studied samples can be categorized into four distinct types or varieties (ΔK = 3.74) such as ND, NN, and HI where AS and JF clustered together as an admixed population. The Neighbor-Joining phylogenetic tree and discriminant analysis of principal component also showed close relatedness among three chicken varieties namely AS, HI, and JF. CONCLUSION: The results reflected that indigenous chicken of Bangladesh still possess rich genetic diversity but weak differentiation among the studied populations. This finding provides some important insight on genetic diversity measures that could support the designing and implementing of future breeding plans for indigenous chickens of Bangladesh.

Genetic diversity of MHC-B in 12 chicken populations in Korea revealed by single-nucleotide polymorphisms.

This study used a single-nucleotide polymorphism (SNP) panel to characterise the diversity in the major histocompatibility complex B region (MHC-B) in 12 chicken populations in Korea. Samples were genotyped for 96 MHC-B SNPs using an Illumina GoldenGate genotyping assay. The MHC-B SNP haplotypes were predicted using 58 informative SNPs and a coalescence-based Bayesian algorithm implemented by the PHASE program and a manual curation process. In total, 117 haplotypes, including 24 shared and 93 unique haplotypes, were identified. The unique haplotype numbers ranged from 0 in Rhode Island Red to 32 in the Korean native commercial chicken population 2 ("Hanhyup-3ho"). Population and haplotype principal component analysis (PCA) indicated no clear population structure based on the MHC haplotypes. Three haplotype clusters (A, B, C) segregated in these populations highlighted the relationship between the haplotypes in each cluster. The sequences from two clusters (B and C) overlapped, whereas the sequences from the third cluster (A) were very different. Overall, native breeds had high genetic diversity in the MHC-B region compared with the commercial breeds. This highlights their immune capabilities and genetic potential for resistance to many different pathogens.

Comparison of prediction accuracy for genomic estimated breeding value using the reference pig population of single-breed and admixed-breed.

This study was performed to increase the accuracy of genomic estimated breeding value (GEBV) predictions for domestic pigs using single-breed and admixed reference populations (single-breed of Berkshire pigs [BS] with cross breed of Korean native pigs and Landrace pigs [CB]). The principal component analysis (PCA), linkage disequilibrium (LD), and genome-wide association study (GWAS) were performed to analyze the population structure prior to genomic prediction. Reference and test population data sets were randomly sampled 10 times each and precision accuracy was analyzed according to the size of the reference population (100, 200, 300, or 400 animals). For the BS population, prediction accuracy was higher for all economically important traits with larger reference population size. Prediction accuracy was ranged from -0.05 to 0.003, for all traits except carcass weight (CWT), when CB was used as the reference population and BS as the test. The accuracy of CB for backfat thickness (BF) and shear force (SF) using admixed population as reference increased with reference population size, while the results for CWT and muscle pH at 24 hours after slaughter (pH) were equivocal with respect to the relationship between accuracy and reference population size, although overall accuracy was similar to that using the BS as the reference.