Eun-Ji Jung

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F(2) intercross between Landrace and Korean native pigs. Eight blood-related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F(2) progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome-wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood-related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker-assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.

Establishment of a Microsatellite Marker Set for Individual, Pork Brand and Product Origin Identification in Pigs

Hyun-Tae Lim*, Bo-Yeong Seo*, Eun-Ji Jung*, Chae-Kyoung Yoo*, Tao Zhong*, In-Cheol Cho**, Duhak Yoon**, Jung-Gyu Lee* and Jin-Tae Jeon*Division of Applied Life Science (BK21 program) Graduate School of Gyeongsang National University*,National Institute of Animal Science, R. D. A.**ABSTRACTSeventeen porcine microsatellite(MS) markers recommended by the EID+DNA Tracing EU project, ISAG and Roslin institute were selected for the use in porcine individual and brand identification. The MSA, CERVUS, FSTAT, GENEPOP and API-CALC programs were applied for calculating heterozygosity indices. By considering the hetreozygosity value and PCR product size of each marker, we established a MS marker set composed of 13 MS markers(SW936, SW951, SW787, S00090, S0026, SW122, SW857, S0005, SW72, S0155, S0225, SW24 and SW632) and two sexing markers. The expected probability of identity among genotypes of random individuals(PI), probability of identity among genotypes from random half sibs(PI

QTL analysis of body weight and carcass body length traits in an F2 intercross between Landrace and Korean native pigs

Growth traits, such as body weight and carcass body length, directly affect productivity and economic efficiency in the livestock industry. We performed a genome-wide linkage analysis to detect the quantitative trait loci (QTL) that affect body weight, growth curve parameters and carcass body length in an F2 intercross between Landrace and Korean native pigs. Eight phenotypes related to growth were measured in approximately 1000 F2 progeny. All experimental animals were subjected to genotypic analysis using 173 microsatellite markers located throughout the pig genome. The least squares regression approach was used to conduct the QTL analysis. For body weight traits, we mapped 16 genome-wide significant QTL on SSC1, 3, 5, 6, 8, 9 and 12 as well as 22 suggestive QTL on SSC2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 16 and 17. On SSC12, we identified a major QTL affecting body weight at 140 days of age that accounted for 4.3% of the phenotypic variance, which was the highest test statistic (F-ratio = 45.6 under the additive model, nominal P = 2.4 × 10(-11) ) observed in this study. We also showed that there were significant QTL on SSC2, 5, 7, 8, 9 and 12 affecting carcass body length and growth curve parameters. Interestingly, the QTL on SSC2, 3, 5, 6, 8, 9, 10, 12 and 17 influencing the growth-related traits showed an obvious trend for co-localization. In conclusion, the identified QTL may play an important role in investigating the genetic structure underlying the phenotypic variation of growth in pigs.

Whole-genome association study for the roan coat color in an intercrossed pig population between Landrace and Korean native pig

The roan coat color is characterized by white hairs intermingled with colored hairs. Candidate genes based on comparative phenotypes in horses and cattle involve the KIT and KIT ligand (MGF) genes. Here, we report the result of the whole genome scanning to detect genomic regions responsible for the roan coat color, using a three-generation pedigree of 62 pigs in an intercross between Landrace and Korean native pig. These pigs were genotyped using the PorcineSNP 60 BeadChip (Illumina, USA). The whole genome scan indicated that three genomic regions, 35∼36 Mb, 38∼39 Mb, and 58∼59 Mb on SSC8, were commonly and highly associated/linked with the roan phenotype in the case/control, sib-pair, and linkage test, respectively. The porcine KIT was selected as a candidate gene, because it is located in one of the three significant regions and its function is related to coat color formation. SNPs and Indels within coding sequence (CDS), promoter, and 3′-UTR of KIT were surveyed. Twenty-two SNPs in the CDS reported previously, as well as nine variations in promoter (2 SNPs) and 3′-UTR (5 SNPs and 2 Indels) were detected. Although no causative mutations were identified, these results will help to elucidate the genetic mechanisms involved in the expression of the roan phenotype and will aid in identifying key mutations responsible for the roan phenotype in further studies.

QTL analysis of clinical-chemical traits in an F2 intercross between Landrace and Korean native pigs

Clinical-chemical traits are essential when examining the health status of individuals. The aim of this study was to identify quantitative trait loci (QTL) and the associated positional candidate genes affecting clinical-chemical traits in a reciprocal F(2) intercross between Landrace and Korean native pigs. Following an overnight fast, 25 serum phenotypes related to clinical-chemical traits (e.g., hepatic function parameters, renal function parameters, electrolyte, lipids) were measured in >970 F(2) progeny. All experimental samples were subjected to genotyping analysis using 165 microsatellite markers located across the genome. We identified eleven genome-wide significant QTL in six chromosomal regions (SSC 2, 7, 8, 13, 14, and 15) and 59 suggestive QTL in 17 chromosomal regions (SSC 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, and 18). We also observed significant effects of reciprocal crosses on some of the traits, which would seem to result from maternal effect, QTL on sex chromosomes, imprinted genes, or genetic difference in mitochondrial DNA. The role of genomic imprinting in clinical-chemical traits also was investigated. Genome-wide analysis revealed a significant evidence for an imprinted QTL in SSC4 affecting serum amylase levels. Additionally, a series of bivariate linkage analysis provided strong evidence that QTL in SSC 2, 13, 15, and 18 have a pleiotropic effect on clinical-chemical traits. In conclusion, our study detected both novel and previously reported QTL influencing clinical-chemical traits in pigs. The identified QTL together with the positional candidate genes identified here could play an important role in elucidating the genetic structure of clinical-chemical phenotype variation in humans and swine.

Genome‐wide association analysis identifies quantitative trait loci for growth in a Landrace purebred population

Growth-related traits are complex and economically important in the livestock industry. The aim of this study was to identify quantitative trait loci (QTL) and the associated positional candidate genes affecting growth in pigs. A genome-wide association study (GWAS) was performed using the porcine single-nucleotide polymorphism (SNP) 60K bead chip. A mixed-effects model and linear regression approach were used for the GWAS. The data used in the study included 490 purebred Landrace pigs. All experimental animals were genotyped with 39 438 SNPs located throughout the pig autosomes. We identified a strong association between a SNP marker on chromosome 16 and body weight at 71 days of age (ALGA0092396, P = 5.35 × 10(-9) , Bonferroni adjusted P < 0.05). The SNP marker was located near the genomic region containing IRX4, which encodes iroquois homeobox 4. This SNP marker could be useful in the selective breeding program after validating its effect on other populations.

Genome-wide QTL analysis of meat quality-related traits in a large F2 intercross between Landrace and Korean native pigs

BackgroundWe conducted a genome-wide linkage analysis to identify quantitative trait loci (QTL) that influence meat quality-related traits in a large F2 intercross between Landrace and Korean native pigs. Thirteen meat quality-related traits of the m. longissimus lumborum et thoracis were measured in more than 830 F2 progeny. All these animals were genotyped with 173 microsatellite markers located throughout the pig genome, and the GridQTL program based on the least squares regression model was used to perform the QTL analysis.ResultsWe identified 23 genome-wide significant QTL in eight chromosome regions (SSC1, 2, 6, 7, 9, 12, 13, and 16) (SSC for Sus Scrofa) and detected 51 suggestive QTL in the 17 chromosome regions. QTL that affect 10 meat quality traits were detected on SSC12 and were highly significant at the genome-wide level. In particular, the QTL with the largest effect affected crude fat percentage and explained 22.5% of the phenotypic variance (F-ratio = 278.0 under the additive model, nominal P = 5.5 × 10−55). Interestingly, the QTL on SSC12 that influenced meat quality traits showed an obvious trend for co-localization.ConclusionsOur results confirm several previously reported QTL. In addition, we identified novel QTL for meat quality traits, which together with the associated positional candidate genes improve the knowledge on the genetic structure that underlies genetic variation for meat quality traits in pigs.

Genome‐wide association study identifies quantitative trait loci affecting hematological traits in an F2 intercross between Landrace and Korean native pigs

Changes affecting the status of health and robustness can bring about physiological alterations including hematological parameters in swine. To identify quantitative trait loci (QTL) associated with eight hematological traits (one leukocyte trait, six erythrocyte traits and one platelet trait), we conducted a genome-wide association study using the PorcineSNP60K BeadChip in a resource population derived from an intercross between Landrace and Korean native pigs. A total of 36 740 SNPs from 816 F2 progeny were analyzed for each blood-related trait after filtering for quality control. Data were analyzed by the genome-wide rapid association using mixed model and regression (GRAMMAR) approach. A total of 257 significant SNPs (P < 1.36 × 10(-6) ) on SSC3, 6, 8, 13 and 17 were identified for blood-related traits in this study. Interestingly, the genomic region between 17.9 and 130 Mb on SSC8 was found to be significantly associated with red blood cell, mean corpuscular volume and mean corpuscular hemoglobin. Our results include the identification of five significant SNPs within five candidate genes (KIT, IL15, TXK, ARAP2 and ERG) for hematopoiesis. Further validation of these identified SNPs could give valuable information for understanding the variation of hematological traits in pigs.

Identification of SNPs Affecting Porcine Carcass Weight with the 60K SNP Chip

ABSTRACT Carcass weight (CW) is one of the most important economic traits in pigs, directly affecting the income of farmers. In this study, a genome wide association study was performed to detect significant single nucleotide polymorphisms (SNPs) affecting CW in pigs derived from a F 2 intercross between Landrace and Korean native pig (KNP). Using high-density porcine SNP chips, highly significant SNPs were identified on SSC12. Two candidate genes, LOC100523510 and LOC100621652 , were subsequently selected within this region and further investigated. Within these candidate genes, five SNPs were identified and genotyped using the VeraCode GoldenGate assay. The results revealed that one SNP in the LOC100621652 gene and four SNPs in the LOC100523510 gene are highly associated with CW. These SNP markers can thus have significant applications for improving CW in KNP. However, the functions of these candidate genes are not fully understood and require further study.( Key words : Candidate gene, Carcass weight, Pig, SNP chip, SSC12)

Cloning, cSNP Identification, and Genotyping of Pig Complement Factor B (CFB) Gene Located on the SLA Class III Region

ABSTRACT The primers for RT-PCR and RACE-PCR were designed by aligning the pig genomic sequence and the human complement factor B (CFB) coding sequence (CDS) from the GenBank. Each PCR product was amplified in pig cDNA and sequencing was carried out. The CDS length of pig CFB gene was determined to be 2298 bp. In addition, the pig CDS was more longer than human and mouse orthologs because of insertion and deletion. The identities of porcine nucleotide sequences with those of human and mice were 84% and 80%, and the identities of amino acids were 79% to 77%, respectively. Three complement control protein (CCP) domains, one Von Willebrand factor A (VWFA) domain and a serine protease domain, that are revealed typically in mammals, were found in the pig CFB gene. Based on the CDSs determined, the primers were designed in intron regions for amplification of entire length of exons. In amplification and direct sequencing with genomic DNAs of six pig breeds, three cSNPs (coding single nucleotide polymorphisms) were identified and verified as missense mutations. Using the Multiplex-ARMS method, we genotyped and verified the mutations identified from direct sequencing. To demonstrate recrudescence, we performed both direct sequencing and Multiplex-ARMS with two randomly selected DNA samples. The genotype of each sample exhibited the same results using both methods. Therefore, three cSNPs were identified from pig CFB gene and that can be used for haplotype analysis of the swine leukocyte antigen(SLA) class III region. Moreover, the results indicate that the Multiplex-ARMS method should be powerful for genotyping of genes in the SLA region.(