• Asian-Australasian Journal of Animal Sciences
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• v.33 no.9
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• pp.1400-1410
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• 2020

Objective: Genome-wide association study and two meta-analysis based on GWAS performed to explore the genetic mechanism underlying variation in pig number born alive (NBA) and total number born (TNB). Methods: Single trait GWAS and two meta-analysis (single-trait meta analysis and multi-trait meta analysis) were used in our study for NBA and TNB on 3,121 Yorkshires from 4 populations, including three different American Yorkshire populations (n = 2,247) and one British Yorkshire populations (n = 874). Results: The result of single trait GWAS showed that no significant associated single nucleotide polymorphisms (SNPs) were identified. Using single-trait meta analysis and multi-trait meta analysis within populations, 11 significant loci were identified associated with target traits. Spindlin 1, vascular endothelial growth factor A, forkhead box Q1, msh homeobox 1, and LHFPL tetraspan submily member 3 are five functionally plausible candidate genes for NBA and TNB. Compared to the single population GWAS, single-trait Meta analysis can improve the detection power to identify SNPs by integrating information of multiple populations. The multiple-trait analysis reduced the power to detect trait-specific loci but enhanced the power to identify the common loci across traits. Conclusion: In total, our findings identified novel genes to be validated as candidates for NBA and TNB in pigs. Also, it enabled us to enlarge population size by including multiple populations with different genetic backgrounds and increase the power of GWAS by using meta analysis.

• Journal of Life Science
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• v.13 no.4
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• pp.375-382
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• 2003

A direct and precise explanation of soybean resistance to soybean cyst nematode will be possible only when the individual gene(s) involved in the resistance are tagged. This study was conducted, (1) to identify and localize quantitative trait loci for resistance to soybean cyst nematode race 14 on RAPD map, (2) to identify the magnitude and mode of inheritance for each quantitative trait loci, and (3) to identify the best combinations of quantitative trait loci for resistance to soybean cyst nematode race 14. Thirty markers (29 RAPD and 1 RFLP) showed significant association with resistance to soybean cyst nematode race 14. From MAPMAKER/QTL analysis, we identified two regions (linkage group C-7 and linkage group C-9) for resistance to soybean cyst nematode .ace 14. The first quantitative trait loci that was localized at 6.0 cM from $H06^1$ on linkage group C-7 showed a dominant inheritance mode. However, we can not exclude the possibility of additive inheritance mode. The second quantitative trait loci that was localized between $B15^2$ and $E01^1$ on linkage group C-9 also showed a dominant mode of inheritance. One pair of flanking markers ($H06^1$ and $H06^2$) and B15$^2$ were used for multiple regression analysis. Marker combination that included 2 markers, $B15^2$ and $H06^1$, explained the highest total variance (22.9%) for resistance to soybean cyst nematode race 14. Further localization of genes for resistance to soybean cyst nematode race 14 and examination of interaction between quantitative trait loci will accelerate the exploitation of resistance to soybean cyst nematode.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.11
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• pp.1505-1510
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• 2001

A method for mapping quantitative trait loci (QTL) was introduced incorporating the information of mixed progeny from complex pedigrees. The method consisted of two steps based on single marker analysis. The first step was to examine the marker-trait association with a mixed model considering common environmental effect and reversed QTL-marker linkage phase. The second step was to estimate QTL effects by a weighted least square analysis. A simulation study indicated that the method incorporating mixed progeny from multiple generations improved the accuracy of QTL detection. The influence of within-genotype variance and recombination rate on QTL analysis was further examined. Detecting a QTL with a large within-genotype variance was more difficult than with a small within-genotype variance. Most of the significant marker-QTL association was detectable when the recombination rate was less than 15%.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.10
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• pp.1406-1410
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• 2014

Age at first calving is an important trait for achieving earlier reproductive performance. To detect quantitative trait loci (QTL) for reproductive traits, a genome wide association study was conducted on the 96 Hanwoo cows that were born between 2008 and 2010 from 13 sires in a local farm (Juk-Am Hanwoo farm, Suncheon, Korea) and genotyped with the Illumina 50K bovine single nucleotide polymorphism (SNP) chips. Phenotypes were regressed on additive and dominance effects for each SNP using a simple linear regression model after the effects of birth-year-month and polygenes were considered. A forward regression procedure was applied to determine the best set of SNPs for age at first calving. A total of 15 QTL were detected at the comparison-wise 0.001 level. Two QTL with strong statistical evidence were found at 128.9 Mb and 111.1 Mb on bovine chromosomes (BTA) 2 and 7, respectively, each of which accounted for 22% of the phenotypic variance. Also, five significant SNPs were detected on BTAs 10, 16, 20, 26, and 29. Multiple QTL were found on BTAs 1, 2, 7, and 14. The significant QTLs may be applied via marker assisted selection to increase rate of genetic gain for the trait, after validation tests in other Hanwoo cow populations.

• Genomics & Informatics
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• v.12 no.4
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• pp.187-194
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• 2014

Metabolic syndrome (METS) is a disorder of energy utilization and storage and increases the risk of developing cardiovascular disease and diabetes. To identify the genetic risk factors of METS, we carried out a genome-wide association study (GWAS) for 2,657 cases and 5,917 controls in Korean populations. As a result, we could identify 2 single nucleotide polymorphisms (SNPs) with genome-wide significance level p-values (< $5{\times}10^{-8}$), 8 SNPs with genome-wide suggestive p-values ($5{\times}10^{-8}{\leq}$ p < $1{\times}10^{-5}$), and 2 SNPs of more functional variants with borderline p-values ($5{\times}10^{-5}{\leq}$ p < $1{\times}10^{-4}$). On the other hand, the multiple correction criteria of conventional GWASs exclude false-positive loci, but simultaneously, they discard many true-positive loci. To reconsider the discarded true-positive loci, we attempted to include the functional variants (nonsynonymous SNPs [nsSNPs] and expression quantitative trait loci [eQTL]) among the top 5,000 SNPs based on the proportion of phenotypic variance explained by genotypic variance. In total, 159 eQTLs and 18 nsSNPs were presented in the top 5,000 SNPs. Although they should be replicated in other independent populations, 6 eQTLs and 2 nsSNP loci were located in the molecular pathways of LPL, APOA5, and CHRM2, which were the significant or suggestive loci in the METS GWAS. Conclusively, our approach using the conventional GWAS, reconsidering functional variants and pathway-based interpretation, suggests a useful method to understand the GWAS results of complex traits and can be expanded in other genomewide association studies.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.4
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• pp.587-596
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• 2001

In the last decade, rapid developments in molecular biotechnology and of genomic tools have enabled the creation of dense linkage maps across whole genomes of human, plant and animals. Successful development and implementation of interval mapping methodologies have allowed detection of the quantitative trait loci (QTL) responsible for economically important traits in experimental and commercial livestock populations. The candidate gene approach can be used in any general population with the availability of a large resource of candidate genes from the human or rodent genomes using comparative maps, and the validated candidate genes can be directly applied to commercial breeds. For the QTL detected from primary genome scans, two incipient fine mapping approaches are applied by generating new recombinants over several generations or utilizing historical recombinants with identity-by-descent (IBD) and linkage disequilibrium (LD) mapping. The high resolution definition of QTL position from fine mapping will allow the more efficient implementation of breeding programs such as marker-assisted selection (MAS) or marker-assisted introgression (MAI), and will provide a route toward cloning the QTL.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.2
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• pp.155-160
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• 2008

Several studies have reported quantitative trait loci (QTL) for meat quality on porcine chromosome 2 (http://www.animalgenome.org/QTLdb/pig.html). For application of the molecular genetic information to the pig industry through marker-assisted selection, single nucleotide polymorphism (SNP) markers were analyzed by comparative re-sequencing of polymerase chain reaction (PCR) products of 13 candidate genes with DNA from commercial pig breeds such as Berkshire, Yorkshire, Landrace, Duroc and Korean Native pig. A total of 34 SNPs were identified in 15 PCR products producing an average of one SNP in every 253 bp. PCR restriction fragment length polymorphism (RFLP) assays were developed for 11 SNPs and used to investigate allele frequencies in five commercial pig breeds in Korea. Eight of the SNPs appear to be fixed in at least one of the five pig breeds, which indicates that different selection among pig breeds might be applied to these SNPs. Polymorphisms detected in the PTH, CSF2 and FOLR genes were chosen to genotype a Berkshire-Yorkshire pig breed reference family for linkage and association analyses. Using linkage analysis, PTH and CSF2 loci were mapped to pig chromosome 2, while FOLR was mapped to pig chromosome 9. Association analyses between SNPs in the PTH, CSF2 and FOLR suggested that the CSF2 MboII polymorphism was significantly associated with several pork quality traits in the Berkshire and Yorkshire crossed F2 pigs. Our current findings provide useful SNP marker information to fine map QTL regions on pig chromosome 2 and to clarify the relevance of SNP and quantitative traits in commercial pig populations.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.10
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• pp.1329-1334
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• 2011

The Hinai-dori is a breed of chicken native to Akita Prefecture, Japan. An $F_2$ resource population produced by crossing low- and high-growth lines of the Hinai-dori breed was analyzed to detect quantitative trait loci (QTL) for growth traits. Highly significant QTLs for body weight at 10 and 14 weeks of age and average daily gain between 4 and 10 weeks and between 10 and 14 weeks of age were accordingly mapped in a common region between ADL0198 and ABR0287 on chromosome 1 and between MCW0240 and ABR0622 on chromosome 4, respectively. A significant QTL for body weight at 4 weeks of age and a significant QTL for average daily gain between 0 and 4 weeks of age were mapped for the first time to the same region flanking ABR0204 and ABR0284 on chromosome 1. These QTLs are good candidates for application in the development of marker-assisted selection strategies for increasing growth efficiencies in the Hinai-dori breed and native breeds of chickens in Asia.

• Asian-Australasian Journal of Animal Sciences
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• v.16 no.3
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• pp.320-324
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• 2003

The objective of this study was to localize QTL affecting meat quality in a pig family of three generations. All animals were genotyped for twenty-four microsatellites on SSC3 (Sus scrofa chromosome 3), SSC4 and SSC7. One hundred and forty $F_2$ offsprings were scored for eleven meat quality traits. Least square regression interval mapping revealed quantitative trait loci (QTL) effect for meat pH (m. Semipinalis Capitis, SC) on SSC4 and SSC7; for moisture (m. Longissimus Dorsi, LD) on SSC3. Furthermore, there was suggestive evidence for a QTL on SSC4 affecting intramuscular fat (IMF) content that nearly approached the chromosomewise (p=0.05) significance threshold.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.7
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• pp.932-937
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• 2002

A partial genome scan using porcine microsatellites was carried out to detect quantitative trait loci (QTL) for backfat thickness (BFT) in a pig reference population. This population carried QTL on chromosomes 1, 13 and 18. The QTL on chromosome 1 was located between marker loci S0113 and SW1301. The QTL corresponded to very low density lipoprotein receptor gene (VLDLR) in location and in biological effects, suggesting that VLDLR might be a candidate gene. The QTL found on chromosome 13 was found between marker loci SWR1941 and SW864, but significance for the marker-trait association was inconsistent by using data with different generations. The QTL on chromosome 18 was discovered between markers S0062 and S0117, and it was in proximity of the regions where IGFBP3 and GHRHR were located. The porcine obese gene might be also a candidate gene for the QTL on chromosome 18. In order to understand genetic architecture of BFT better, fine mapping and positional comparative candidate gene analyses are necessary.