Application of deep learning with bivariate models for genomic prediction of sow lifetime productivity-related traits.

OBJECTIVE: Pig breeders cannot obtain phenotypic information at the time of selection for sow lifetime productivity (SLP). They would benefit from obtaining genetic information of candidate sows. Genomic data interpreted using deep learning (DL) techniques could contribute to the genetic improvement of SLP to maximize farm profitability because DL models capture nonlinear genetic effects such as dominance and epistasis more efficiently than conventional genomic prediction methods based on linear models. This study aimed to investigate the usefulness of DL for the genomic prediction of two SLP-related traits; lifetime number of litters (LNL) and lifetime pig production (LPP). METHODS: Two bivariate DL models, convolutional neural network (CNN) and local convolutional neural network (LCNN), were compared with conventional bivariate linear models (i.e., genomic best linear unbiased prediction, Bayesian ridge regression, Bayes A, and Bayes B). Phenotype and pedigree data were collected from 40,011 sows that had husbandry records. Among these, 3,652 pigs were genotyped using the PorcineSNP60K BeadChip. RESULTS: The best predictive correlation for LNL was obtained with CNN (0.28), followed by LCNN (0.26) and conventional linear models (approximately 0.21). For LPP, the best predictive correlation was also obtained with CNN (0.29), followed by LCNN (0.27) and conventional linear models (approximately 0.25). A similar trend was observed with the mean squared error of prediction for the SLP traits. CONCLUSION: This study provides an example of a CNN that can outperform against the linear model-based genomic prediction approaches when the nonlinear interaction components are important because LNL and LPP exhibited strong epistatic interaction components. Additionally, our results suggest that applying bivariate DL models could also contribute to the prediction accuracy by utilizing the genetic correlation between LNL and LPP.

Individual and population diversity of 20 representative olfactory receptor genes in pigs.

Understanding the influence of genetic variations in olfactory receptor (OR) genes on the olfaction-influenced phenotypes such as behaviors, reproduction, and feeding is important in animal biology. However, our understanding of the complexity of the OR subgenome is limited. In this study, we analyzed 1120 typing results of 20 representative OR genes belonging to 13 OR families on 14 pig chromosomes from 56 individuals belonging to seven different breeds using a sequence-based OR typing method. We showed that the presence of copy number variations, conservation of locus-specific diversity, abundance of breed-specific alleles, presence of a loss-of-function allele, and low-level purifying selection in pig OR genes could be common characteristics of OR genes in mammals. The observed nucleotide sequence diversity of pig ORs was higher than that of dogs. To the best of our knowledge, this is the first report on the individual- or population-level characterization of a large number of OR family genes in livestock species.

Knockdown of Y-box binding protein 1 induces autophagy in early porcine embryos.

Y-box binding protein 1 (YBX1) plays important roles in RNA stabilization, translation, transcriptional regulation, and mitophagy. However, its effects on porcine preimplantation embryos remain unclear. In this study, we knocked down YBX1 in the one-cell (1C) stage embryo via small interfering RNA microinjection to determine its function in porcine embryo development. The mRNA level of YBX1 was found to be highly expressed at the four-cell (4C) stage in porcine embryos compared with one-cell (1C) and two-cell (2C) stages. The number of blastocysts was reduced following YBX1 knockdown. Notably, YBX1 knockdown decreased the phosphatase and tensin homolog-induced kinase 1 (PINK1) and parkin RBR E3 ubiquitin protein ligase (PRKN) mRNA levels. YBX1 knockdown also decreased PINK1, active mitochondria, and sirtuin 1 levels, indicating reduced mitophagy and mitochondrial biogenesis. Furthermore, YBX1 knockdown increased the levels of glucose-regulated protein 78 (GRP78) and calnexin, leading to endoplasmic reticulum (ER) stress. Additionally, YBX1 knockdown increased autophagy and apoptosis. In conclusion, knockdown of YBX1 decreases mitochondrial function, while increasing ER stress and autophagy during embryonic development.

Profiling of differentially expressed proteins between fresh and frozen-thawed Duroc boar semen using ProteinChip CM10.

Many studies have been conducted to improve technology for semen cryopreservation in pigs. However, computer-assisted analysis of sperm motility and morphology is insufficient to predict the molecular function of frozen-thawed semen. More accurate expression patterns of boar sperm proteins may be derived using the isobaric tags for relative and absolute quantification (iTRAQ) technique. In this study, the iTRAQ-labeling system was coupled with liquid chromatography tandem-mass spectrometry (LC-MS/MS) analysis to identify differentially expressed CM10-fractionated proteins between fresh and frozen-thawed boar semen. A total of 76 protein types were identified to be differentially expressed, among which 9 and 67 proteins showed higher and lower expression in frozen-thawed than in fresh sperm samples, respectively. The classified functions of these proteins included oxidative phosphorylation, mitochondrial inner membrane and matrix, and pyruvate metabolic processes, which are involved in adenosine triphosphate (ATP) synthesis; and sperm flagellum and motile cilium, which are involved in sperm tail structure. These results suggest a possible network of biomarkers associated with survival after the cryopreservation of Duroc boar semen.

An intelligent method for pregnancy diagnosis in breeding sows according to ultrasonography algorithms.

Pig breeding management directly contributes to the profitability of pig farms, and pregnancy diagnosis is an important factor in breeding management. Therefore, the need to diagnose pregnancy in sows is emphasized, and various studies have been conducted in this area. We propose a computer-aided diagnosis system to assist livestock farmers to diagnose sow pregnancy through ultrasound. Methods for diagnosing pregnancy in sows through ultrasound include the Doppler method, which measures the heart rate and pulse status, and the echo method, which diagnoses by amplitude depth technique. We propose a method that uses deep learning algorithms on ultrasonography, which is part of the echo method. As deep learning-based classification algorithms, Inception-v4, Xception, and EfficientNetV2 were used and compared to find the optimal algorithm for pregnancy diagnosis in sows. Gaussian and speckle noises were added to the ultrasound images according to the characteristics of the ultrasonography, which is easily affected by noise from the surrounding environments. Both the original and noise added ultrasound images of sows were tested together to determine the suitability of the proposed method on farms. The pregnancy diagnosis performance on the original ultrasound images achieved 0.99 in accuracy in the highest case and on the ultrasound images with noises, the performance achieved 0.98 in accuracy. The diagnosis performance achieved 0.96 in accuracy even when the intensity of noise was strong, proving its robustness against noise.

Parabacteroides faecalis sp. nov. Isolated from Swine Faeces.

A Gram-negative, obligate anaerobic, non-motile, non-spore-forming, rod-shaped bacterial strain designated AGMB00274T was isolated from swine faeces. An 16S rRNA gene analysis indicated that strain AGMB00274T belonged to the genus Parabacteroides, with the highest similarity to Parabacteroides johnsonii (P. johnsonii) DSM 18315T (sequence similarity of 94.9%). The genome size of strain AGMB00274T was 4,308,683 bp, with a DNA G+C content of 42.5 mol%. The biochemical analysis of strain AGMB00274T showed that it was positive for gelatin hydrolysis and α-fucosidase, but negative for the acid production from D-glucose, D-mannitol, D-maltose, salicin, glycerol, D-cellobiose, D-mannose, D-melezitose, D-sorbitol, D-trehalose, and negative for α-arabinosidase, glutamic acid decarboxylase, and pyroglutamic acid arylamidase. The dominant cellular fatty acids (> 10%) of the isolate were anteiso-C15: 0 (23.2%), iso-C15: 0 (16.6%), C18: 1 ω9c (16.4%), summed feature 11 (iso-C17: 0 3-OH and/or C18: 2 DMA) (12.5%), and C16: 0 (11.3%). The major respiratory quinones of strain AGMB00274T were MK-9 (55.4%) and MK-10 (44.6%). The major polar lipid was phosphatidylethanolamine. Based on phylogenetic, genetic, physiological, and chemotaxonomic analyses, as a novel species of the genus Parabacteroides, strain AGMB00274T was proposed with the name Parabacteroides faecalis sp. nov. The type strain used was AGMB00274T (= KCTC 25286T = GDMCC 1.2742T).

Population differentiated copy number variation between Eurasian wild boar and domesticated pig populations.

Sus scrofa is a globally distributed livestock species that still maintains two different ways of life: wild and domesticated. Herein, we detected copy number variation (CNV) of 328 animals using short read alignment on Sscrofa11.1. We compared CNV among five groups of porcine populations: Asian domesticated (AD), European domesticated (ED), Asian wild (AW), European wild (EW), and Near Eastern wild (NEW). In total, 21,673 genes were identified on 154,872 copy number variation region (CNVR). Differences in gene copy numbers between populations were measured by considering the variance-based value [Formula: see text] and the one-way ANOVA test followed by Scheffe test. As a result, 111 genes were suggested as copy number variable genes. Abnormally gained copy number on EEA1 in all populations was suggested the presence of minor CNV in the reference genome assembly, Sscrofa11.1. Copy number variable genes were related to meat quality, immune response, and reproduction traits. Hierarchical clustering of all individuals and mean pairwise [Formula: see text] in breed level were visualized genetic relationship of 328 individuals and 56 populations separately. Our findings have shown how the complex history of pig evolution appears in genome-wide CNV of various populations with different regions and lifestyles.

Genetic Parameter Estimation and Genome-Wide Association Analysis of Social Genetic Effects on Average Daily Gain in Purebreds and Crossbreds.

Average daily gain (ADG) is an important growth trait in the pig industry. The direct genetic effect (DGE) has been studied mainly to assess the association between genetic information and economic traits. The social genetic effect (SGE) has been shown to affect ADG simultaneously with the DGE because of group housing systems. We conducted this study to elucidate the genetic characteristics and relationships of the DGE and SGE of purebred Korean Duroc and crossbred pigs by single-step genomic best linear unbiased prediction and a genome-wide association study. We used the genotype, phenotype, and pedigree data of 1779, 6022, and 7904 animals, respectively. Total heritabilities on ADG were 0.19 ± 0.04 and 0.39 ± 0.08 for purebred and crossbred pigs, respectively. The genetic correlation was the greatest (0.77 ± 0.12) between the SGE of purebred and DGE of crossbred pigs. We found candidate genes located in the quantitative trait loci (QTLs) for the SGE that were associated with behavior and neurodegenerative diseases, and candidate genes in the QTLs for DGE that were related to body mass, size of muscle fiber, and muscle hypertrophy. These results suggest that the genomic selection of purebred animals could be applied for crossbred performance.

Integrative methylome and transcriptome analysis of porcine abdominal fat indicates changes in fat metabolism and immune responses during different development.

Fat is involved in synthesizing fatty acids (FAs), FA circulation, and lipid metabolism. Various genetic studies have been conducted on porcine fat but understanding the growth and specific adipose tissue is insufficient. The purpose of this study is to investigate the epigenetic difference in abdominal fat according to the growth of porcine. The samples were collected from the porcine abdominal fat of different developmental stages (10 and 26 weeks of age). Then, the samples were sequenced using MBD-seq and RNA-seq for profiling DNA methylation and RNA expression. In 26 weeks of age pigs, differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified as 2,251 and 5,768, compared with 10 weeks of age pigs, respectively. Gene functional analysis was performed using GO and KEGG databases. In functional analysis results of DMGs and DEGs, immune responses such as chemokine signaling pathways, B cell receptor signaling pathways, and lipid metabolism terms such as PPAR signaling pathways and fatty acid degradation were identified. It is thought that there is an influence between DNA methylation and gene expression through changes in genes with similar functions. The effects of DNA methylation on gene expression were investigated using cis-regulation and trans-regulation analysis to integrate and interpret different molecular layers. In the cis-regulation analysis using 629 overlapping genes between DEGs and DMGs, immune response functions were identified, while in trans-regulation analysis through the TF-target gene network, the co-expression network of lipid metabolism-related functions was distinguished. Our research provides an understanding of the underlying mechanisms for epigenetic regulation in porcine abdominal fat with aging.

Fat is involved in the synthesis of new fatty acids (FAs), FA circulation, and lipid metabolism. Various genetic studies have been conducted on porcine fat but understanding the growth and specific adipose tissue is insufficient. The purpose of this study is to investigate the epigenetic difference in abdominal fat according to the growth of porcine. Modifications in DNA methylation and expression values were confirmed epigenetically with growth. Changed genes in each DNA and RNA showed identical trends in the function of immune response and lipid metabolism. The effects of DNA methylation on gene expression were investigated using cis-regulation (functional enrichment analysis of overlapping genes) and trans-regulation (transcription factor and target gene networking) analysis to integrate and interpret different molecular layers. Our research provides an understanding of the underlying mechanisms for epigenetic regulation in porcine abdominal fat with aging.

Genome-Wide Assessment of a Korean Composite Pig Breed, Woori-Heukdon.

A Korean synthetic pig breed, Woori-Heukdon (WRH; F3), was developed by crossing parental breeds (Korean native pig [KNP] and Korean Duroc [DUC]) with their crossbred populations (F1 and F2). This study in genome-wide assessed a total of 2,074 pigs which include the crossbred and the parental populations using the Illumina PorcineSNP60 BeadChip. After quality control of the initial datasets, we performed population structure, genetic diversity, and runs of homozygosity (ROH) analyses. Population structure analyses showed that crossbred populations were genetically influenced by the parental breeds according to their generation stage in the crossbreeding scheme. Moreover, principal component analysis showed the dispersed cluster of WRH, which might reflect introducing a new breeding group into the previous one. Expected heterozygosity values, which were used to assess genetic diversity, were .365, .349, .336, .330, and .211 for WRH, F2, F1, DUC, and KNP, respectively. The inbreeding coefficient based on ROH was the highest in KNP (.409), followed by WRH (.186), DUC (.178), F2 (.107), and F1 (.035). Moreover, the frequency of short ROH decreased according to the crossing stage (from F1 to WRH). Alternatively, the frequency of medium and long ROH increased, which indicated recent inbreeding in F2 and WRH. Furthermore, gene annotation of the ROH islands in WRH that might be inherited from their parental breeds revealed several interesting candidate genes that may be associated with adaptation, meat quality, production, and reproduction traits in pigs.

A computer vision-based approach for behavior recognition of gestating sows fed different fiber levels during high ambient temperature.

The objectives of this study were to evaluate convolutional neural network models and computer vision techniques for the classification of swine posture with high accuracy and to use the derived result in the investigation of the effect of dietary fiber level on the behavioral characteristics of the pregnant sow under low and high ambient temperatures during the last stage of gestation. A total of 27 crossbred sows (Yorkshire × Landrace; average body weight, 192.2 ± 4.8 kg) were assigned to three treatments in a randomized complete block design during the last stage of gestation (days 90 to 114). The sows in group 1 were fed a 3% fiber diet under neutral ambient temperature; the sows in group 2 were fed a diet with 3% fiber under high ambient temperature (HT); the sows in group 3 were fed a 6% fiber diet under HT. Eight popular deep learning-based feature extraction frameworks (DenseNet121, DenseNet201, InceptionResNetV2, InceptionV3, MobileNet, VGG16, VGG19, and Xception) used for automatic swine posture classification were selected and compared using the swine posture image dataset that was constructed under real swine farm conditions. The neural network models showed excellent performance on previously unseen data (ability to generalize). The DenseNet121 feature extractor achieved the best performance with 99.83% accuracy, and both DenseNet201 and MobileNet showed an accuracy of 99.77% for the classification of the image dataset. The behavior of sows classified by the DenseNet121 feature extractor showed that the HT in our study reduced (p < 0.05) the standing behavior of sows and also has a tendency to increase (p = 0.082) lying behavior. High dietary fiber treatment tended to increase (p = 0.064) lying and decrease (p < 0.05) the standing behavior of sows, but there was no change in sitting under HT conditions.

Genetic relationship between purebred and synthetic pigs for growth performance using single step method.

OBJECTIVE: The objective of this study was to estimate the genetic correlation (rpc) of growth performance between purebred (Duroc and Korean native) and synthetic (WooriHeukDon) pigs using a single-step method. METHODS: Phenotypes of 15,902 pigs with genotyped data from 1,792 pigs from a nucleus farm were used for this study. We estimated the rpc of several performance traits between WooriHeukDon and purebred pigs: day of target weight (DAY), backfat thickness (BF), feed conversion rate (FCR), and residual feed intake (RFI). The variances and covariances of the studied traits were estimated by an animal multi-trait model that applied the Bayesian inference. RESULTS: rpc within traits was lower than 0.1 for DAY and BF, but high for FCR and RFI; in particular, rpc for RFI between Duroc and WooriHeukDon pigs was nearly 1. Comparison between different traits revealed that RFI in Duroc pigs was associated with different traits in WooriHeukDon pigs. However, the most of rpc between different traits were estimated with low or with high standard deviation. CONCLUSION: The results indicated that there were substantial differences in rpc of traits in the synthetic WooriHeukDon pigs, which could be caused by these pigs having a more complex origin than other crossbred pigs. RFI was strongly correlated between Duroc and WooriHeukDon pigs, and these breeds might have similar single nucleotide polymorphism effects that control RFI. RFI is more essential for metabolism than other growth traits and these metabolic characteristics in purebred pigs, such as nutrient utilization, could significantly affect those in synthetic pigs. The findings of this study can be used to elucidate the genetic architecture of crossbred pigs and help develop new breeds with target traits.

Genome-wide investigation of a Korean synthetic breed, Woori-Heukdon using the Illumina PorcineSNP60K BeadChip.

BACKGROUND: Woori-Heukdon (KWH) is a Korean synthetic pig breed generated using Chookjin-Duroc (KCD), Chookjin-Chamdon (KCC), and their crossbreds. Currently, there is a severe lack of studies investigating the Korean breed populations including wild boars (KWB) throughout the genome. OBJECTIVE: This study was performed to investigate the genetic characteristics of Korean pig populations at the genome-wide level. METHODS: Using the SNP dataset derived from genotyped and downloaded datasets using the Illumina PorcineSNP60K BeadChip, we compared the genomes of 532 individuals derived from 23 pig breeds to assess the genetic diversity, inbreeding coefficient, genetic differentiation, and population structure. RESULTS: KWB showed the lowest average expected heterozygosity (HE = 0.1904), while KWH showed the highest genetic diversity (HE = 0.02859) among Korean populations. We verified that the genetic composition of KWH, showing USD of 74.8% and KCC of 25.2% in ADMIXTURE analysis. In population structure analyses, KCC was consistently shown to be separated from other pig populations. In addition, we observed gene flow from Western pigs to a part of Chinese populations. CONCLUSION: This study showed that Korean native pigs, KCC have genetic differences in comparison with Chinese and Western pigs; despite some historical records and recent genetic studies, we could not find any clear evidence that KCC was significantly influenced by Chinese or Western breeds in this study. We also verified the theoretical genomic composition of KWH at the molecular level in structure analyses. To our knowledge, this is the first genomic study to investigate the genomic characteristics of KWH and KCC.

Effects of Zinc Oxide and Arginine on the Intestinal Microbiota and Immune Status of Weaned Pigs Subjected to High Ambient Temperature.

This study aimed to investigate the effect of the l-arginine (Arg) inclusion and different doses of ZnO on the growth performance, intestinal microbiota and integrity, and immune status of weaned pigs. A total of 180 pigs (28-day-old) were randomly allotted to six treatments with six replicate pens in each treatment and five pigs per pen. The dietary treatments were Con (1.1% Arg); P-Zn (1.1% Arg + 2500 mg Zn as ZnO/kg diet); ARG (1.6% Arg); ZnArg1 (500 mg of Zn as ZnO/kg diet + 1.6% Arg); ZnArg2 (1000 mg of Zn as ZnO/kg diet + 1.6% Arg); ZnArg3 (2500 mg of Zn as ZnO/kg diet + 1.6% Arg). The overall result showed that the inclusion of ZnArg3 significantly improved the average daily gain of pigs compared with the Con treatment. There was a reduction in feed intake in pigs fed the Con diet compared with pigs fed the ZnArg3 diet at phase 1 and overall. At phase 1, pigs fed the ZnArg3 diet and P-Zn diet showed a decreased population of Clostridium spp. in the ileum compared with those of the Con treatment. In addition, a lower ileal Clostridium spp. population was detected in pigs fed the ZnArg2 diet compared with pigs fed the Con diet. The pigs fed ZnArg1 and ZnArg3 diets showed a greater villus height of duodenum compared with the Con and P-Zn treatments. The pigs in the Con treatment showed increased mRNA expression of heat shock protein-27 in the liver compared with the P-Zn, ZnArg1, ZnArg2, and ZnArg3 treatments. When fed the basal diet, mRNA expressions of interleukin-6 were increased in the muscle compared with the ZnArg3 treatment. Dietary supplementation with ZnArg2 decreased the mRNA expressions of interferon-γ in the muscle compared with the Con treatment. Supplementation with P-Zn, ZnArg1, ZnArg2, and ZnArg3 decreased mRNA expressions of tumor necrosis factor-α (TNF-α) compared with the Con treatment. The mRNA gene expressions of interleukin-4 were decreased in the jejunum of pigs fed P-Zn, ARG, ZnArg1, ZnArg2, and ZnArg3 diets compared with pigs fed the Con diet. The jejunum gene expression of toll-like receptor-4 was upregulated in the Con and ARG treatments compared with the ZnArg1 and ZnArg3. The ZnArg1, ZnArg2, and ZnArg3 treatments showed lower mRNA expression of TNF-α compared with the Con treatment. In conclusion, there was no difference in growth performance, intestinal microbiota, gene expression of interleukins between ZnArg1 and ZnArg3 treatments. Therefore, the low level of ZnO (500 mg/kg) plus 1.6% dietary Arg may be recommended for pigs during the weaning stress.

Single-step genome-wide association study for social genetic effects and direct genetic effects on growth in Landrace pigs.

In livestock social interactions, social genetic effects (SGE) represent associations between phenotype of one individual and genotype of another. Such associations occur when the trait of interest is affected by transmissible phenotypes of social partners. The aim of this study was to estimate SGE and direct genetic effects (DGE, genetic effects of an individual on its own phenotype) on average daily gain (ADG) in Landrace pigs, and to conduct single-step genome-wide association study using SGE and DGE as dependent variables to identify quantitative trait loci (QTLs) and their positional candidate genes. A total of 1,041 Landrace pigs were genotyped using the Porcine SNP 60K BeadChip. Estimates of the two effects were obtained using an extended animal model. The SGE contributed 16% of the total heritable variation of ADG. The total heritability estimated by the extended animal model including both SGE and DGE was 0.52. The single-step genome-wide association study identified a total of 23 QTL windows for the SGE on ADG distributed across three chromosomes (i.e., SSC1, SSC2, and SSC6). Positional candidate genes within these QTL regions included PRDM13, MAP3K7, CNR1, HTR1E, IL4, IL5, IL13, KIF3A, EFHD2, SLC38A7, mTOR, CNOT1, PLCB2, GABRR1, and GABRR2, which have biological roles in neuropsychiatric processes. The results of biological pathway and gene network analyses also support the association of the neuropsychiatric processes with SGE on ADG in pigs. Additionally, a total of 11 QTL windows for DGE on ADG in SSC2, 3, 6, 9, 10, 12, 14, 16, and 17 were detected with positional candidate genes such as ARL15. We found a putative pleotropic QTL for both SGE and DGE on ADG on SSC6. Our results in this study provide important insights that can help facilitate a better understanding of the molecular basis of SGE for socially affected traits.

The effects of breed and gender on meat quality of Duroc, Pietrain, and their crossbred.

This study evaluated the effects of breed and gender in Duroc (D), Pietrain (P), and crossbred (DP) pigs. Loin samples were collected from D (n = 79), P (n = 42), and DP (n = 45) pigs. Intramuscular fat content was significantly lower in P (p < 0.001), and pH was lowest in DP pigs (p < 0.001). Gilts had higher intramuscular fat (IMF) and pH values than did castrated males (p < 0.05). Water-holding capacity was lower in DP pigs than that in D and P pigs (p < 0.001). Shear force in DP pigs was higher than that in D and P pigs (p < 0.001). Lightness and yellowness of meat in DP pigs was increased compared with coloring of P pig meat (p < 0.01). Meat from DP pigs was redder compared with meat from in D and P pigs, and it was higher in gilts than in castrates (p < 0.001). The C16:0 content was lower in P and DP pigs than in D pigs (p < 0.01). C18:2 content was higher in P and DP pigs than in D pigs (p < 0.001). Unsaturated and saturated fatty acids increased in P pigs compared with levels in D pigs (p < 0.05). Our results suggest that meat quality can be controlled by crossbreeding to increase or reduce selected properties. This study provides the basic data on the meat characteristics of F1 DP pigs. Thus, further study should be conducted to estimate the meat quality of various crossbreeds.

Genetic Diversity and Ancestral Study for Korean Native Pigs Using 60K SNP Chip.

The Korean native pig (KNP; Sus scrofa coreanus) is an indigenous porcine breed in South Korea considered as a valuable but dwindling genetic resource. Studies using diverse methodologies and genetic markers suggest that this population originated from the Manchu province of Northeastern China and migrated approximately 3000 years ago into the Korean peninsula. This study aimed to verify those findings by performing diversity and ancestral analyses using the 60K single-nucleotide polymorphism (SNP) BeadChip on 891 pigs of 47 breeds worldwide. We also performed principal component analysis (PCA), ancestry analyses, phylogenetic tree analysis using SNPhylo, and linkage disequilibrium analysis. Furthermore, we generated heatmap, obtained Nei's genetic distance and FST values, and explored the heterozygosity of commercial and native Korean pigs. The results demonstrated that KNP pigs are more closely related to European breeds than to Chinese breeds. In addition, as previous studies have suggested, our admixture analyses indicated that KNP pigs showed distinguishable genetic structure.

Whole-genome resequencing analysis of 20 Micro-pigs.

BACKGROUND: Miniature pigs have been increasingly used as mammalian model animals for biomedical research because of their similarity to human beings in terms of their metabolic features and proportional organ sizes. However, despite their importance, there is a severe lack of genome-wide studies on miniature pigs. OBJECTIVE: In this study, we performed whole-genome sequencing analysis of 20 Micro-pigs obtained from Medi Kinetics to elucidate their genomic characteristics. RESULTS: Approximately 595 gigabase pairs (Gb) of sequence reads were generated to be mapped to the swine reference genome assembly (Sus scrofa 10.2); on average, the sequence reads covered 99.15% of the reference genome at an average of 9.6-fold coverage. We detected a total of 19,518,548 SNPs, of which 8.7% were found to be novel. With further annotation of all of the SNPs, we retrieved 144,507 nonsynonymous SNPs (nsSNPs); of these, 5968 were found in all 20 individuals used in this study. SIFT prediction for these SNPs identified that 812 nsSNPs in 402 genes were deleterious. Among these 402 genes, we identified some genes that could potentially affect traits of interest in Micro-pigs, such as RHEB and FRAS1. Furthermore, we performed runs of homozygosity analysis to locate potential selection signatures in the genome, detecting several loci that might be involved in phenotypic characteristics in Micro-pigs, such as MSTN, GDF5, and GDF11. CONCLUSION: In this study, we identified numerous nsSNPs that could be used as candidate genetic markers with involvement in traits of interest. Furthermore, we detected putative selection footprints that might be associated with recent selection applied to miniature pigs.

Application of single-step genomic evaluation using social genetic effect model for growth in pig.

OBJECTIVE: Social genetic effects (SGE) are an important genetic component for growth, group productivity, and welfare in pigs. The present study was conducted to evaluate i) the feasibility of the single-step genomic best linear unbiased prediction (ssGBLUP) approach with the inclusion of SGE in the model in pigs, and ii) the changes in the contribution of heritable SGE to the phenotypic variance with different scaling ω constants for genomic relationships. METHODS: The dataset included performance tested growth rate records (average daily gain) from 13,166 and 21,762 pigs Landrace (LR) and Yorkshire (YS), respectively. A total of 1,041 (LR) and 964 (YS) pigs were genotyped using the Illumina PorcineSNP60 v2 BeadChip panel. With the BLUPF90 software package, genetic parameters were estimated using a modified animal model for competitive traits. Giving a fixed weight to pedigree relationships (τ: 1), several weights (ωxx, 0.1 to 1.0; with a 0.1 interval) were scaled with the genomic relationship for best model fit with Akaike information criterion (AIC). RESULTS: The genetic variances and total heritability estimates (T2) were mostly higher with ssGBLUP than in the pedigree-based analysis. The model AIC value increased with any level of ω other than 0.6 and 0.5 in LR and YS, respectively, indicating the worse fit of those models. The theoretical accuracies of direct and social breeding value were increased by decreasing ω in both breeds, indicating the better accuracy of ω0.1 models. Therefore, the optimal values of ω to minimize AIC and to increase theoretical accuracy were 0.6 in LR and 0.5 in YS. CONCLUSION: In conclusion, single-step ssGBLUP model fitting SGE showed significant improvement in accuracy compared with the pedigree-based analysis method; therefore, it could be implemented in a pig population for genomic selection based on SGE, especially in South Korean populations, with appropriate further adjustment of tuning parameters for relationship matrices.