• Asian-Australasian Journal of Animal Sciences
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• v.23 no.10
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• pp.1261-1267
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• 2010

Milk production traits are important economic traits for dairy cattle. The aim of the present study was to refine the position of previously detected quantitative trait loci (QTL) on bovine chromosome 6 affecting milk production traits in Chinese Holstein dairy cattle. A daughter design with 918 daughters from 8 elite sire families and 14 markers spanning the previously identified QTL region were used in the analysis. We employed a combined linkage and linkage disequilibrium analysis (LDLA) approach with two options for calculating the IBD probabilities, one was based on haplotypes of all 14 markers (named Method 1) and the other based on haplotypes with sliding windows of 5 markers (named Method 2). For milk fat yield, the two methods revealed a highly significant QTL located within a 6.5 cM interval (Method 1) and a 4.0 cM interval (Method 2), respectively. For milk protein yield, a highly significant QTL was detected within a 3.0 cM interval (Method 1) or a 2.5 cM interval (Method 2). These results confirmed the findings of our previous study and other studies, and greatly narrowed down the QTL positions.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.5
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• pp.638-642
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• 2017

Objective: This study aimed to validate the statistical evidence from the genome-wide association study (GWAS) as true-positive and to better understand the effects of the glycophorin C (GYPC) gene on serum hemoglobin traits. Methods: Our initial GWAS revealed the presence of two single nucleotide polymorphisms (SNPs) (ASGA0069038 and ALGA0084612) for the hemoglobin concentration trait (HGB) in the 2.48 Mb region of SSC15. From this target region, GYPC was selected as a promising gene that associated with serum HGB traits in pigs. SNPs within the GYPC gene were detected by sequencing. Thereafter, we performed association analysis of the variant with the serum hemoglobin level in three pig populations. Results: We identified one SNP (g.29625094 T>C) in exon 3 of the GYPC gene. Statistical analysis showed a significant association of the SNP with the serum hemoglobin level on day 20 (p<0.05). By quantitative real-time polymerase chain reaction, the GYPC gene was expressed in eight different tissues. Conclusion: These results might improve our understanding of GYPC function and provide evidence for its association with serum hemoglobin traits in the pig. These results also indicate that the GYPC gene might serve as a useful marker in pig breeding programs.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.43-43
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• 2019

The collection, evaluation and conservation of crop germplasm have been treated as one of the basics to breeding program. An understanding of genetic relationships among germplasm resources is vital for future breeding process like yield, quality, and resistance. In the present study, EST-SSR markers were employed to assess the polymorphism and genetic diversity of 192 accessions of Proso millet preserved in the National Agrobiodiversity Center of RDA. We evaluated the efficiency of EST-SSR markers developed for proso millet species. A total of 98 alleles were detected with an average allele number of 4.5 per locus among 192 proso millet millet accessions using 22 EST-SSR markers. The averaged values of gene diversity ($H_E$) and polymorphism information content (PIC) for each EST-SSR marker were 0.362 and 0.404 within populations, respectively. Our results showed the moderate level of the molecular diversity among the proso millet accessions from diverse countries. A phylogenetic tree revealed three major groups of accessions that did not correspond with geographical distribution patterns with a few exceptions. The less correlation between the clusters and their geographic location might be considered due to their type difference. Our study provided a better understanding of genetic relationships among various germplasm collections, and it could contribute to more efficient utilization of valuable genetic resources. The EST-SSR markers developed here will serve as a valuable resource for genetic studies, like linkage mapping, diversity analysis, quantitative trait locus/association mapping, and molecular breeding.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.5
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• pp.607-613
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• 2019

Objective: Intramuscular fat (IMF) content plays an important role in meat quality. Identification of single nucleotide polymorphisms (SNPs) and genes related to pig IMF, especially using pig populations with high IMF content variation, can help to establish novel molecular breeding tools for optimizing IMF in pork and unveil the mechanisms that underlie fat metabolism. Methods: We collected muscle samples of 453 Chinese Lulai black pigs, measured IMF content by Soxhlet petroleum-ether extraction method, and genotyped genome-wide SNPs using GeneSeek Genomic Profiler Porcine HD BeadChip. Then a genome-wide association study was performed using a linear mixed model implemented in the GEMMA software. Results: A total of 43 SNPs were identified to be significantly associated with IMF content by the cutoff p<0.001. Among these significant SNPs, the greatest number of SNPs (n = 19) were detected on Chr.9, and two linkage disequilibrium blocks were formed among them. Additionally, 17 significant SNPs are mapped to previously reported quantitative trait loci (QTLs) of IMF and confirmed previous QTLs studies. Forty-two annotated genes centering these significant SNPs were obtained from Ensembl database. Overrepresentation test of pathways and gene ontology (GO) terms revealed some enriched reactome pathways and GO terms, which mainly involved regulation of basic material transport, energy metabolic process and signaling pathway. Conclusion: These findings improve our understanding of the genetic architecture of IMF content in pork and facilitate the follow-up study of fine-mapping genes that influence fat deposition in muscle.

• Journal of Animal Science and Technology
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• v.55 no.1
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• pp.1-6
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• 2013

This study was aimed to solve the problems of current national genetic evaluation systems in Korea and its development to pass the verification processes as required by International Bull Evaluation Service (Interbull). This will enable Korea to participate in international genetic evaluation program. A total of 1,416,589 test-day milk records with calving dates used in this study were collected by National Agricultural Cooperative Federation from 2001 to 2009. Parity was limited up to fifth calving and milk production records were adjusted to cumulative 305 day lactation. The pedigree consisted of 2,279,741 animals where 2,467 bulls had 535,409 parents. A newly developed multiple trait model was used in calculation of breeding values for milk yield, milk fat, and protein yield. Data were edited with SAS (version 9.2) and R programs, and genetic parameters were estimated using VCE 6.0. Results showed a continuous increase in genetic potentials, in general, and no remarkable differences were found between performances by parity. Except fat yield, potentials in milk yield and protein yield were well calculated. We found an increased number of daughters per each top ranked 1,000 bulls in recent years of calf births compared to the cases of previous evaluations. Of the bulls ranked top 100 by our new models (multiple-trait models) we found that increased numbers of bulls were included. Of twenty eight bulls born in 2006, twenty bulls born in 2007 and eight bulls born in 2008 that were listed by new models, only 23, 12, and 2 bulls born in respective years were represented on top 100 by old single-trait models. Re-ranking of the daughters or sires by multiple-trait models suggest that this new multiple trait approach should be used for dairy cattle genetic evaluation and seed-stock selection in the future to increase the accuracy of multiple trait selection. Breeding values for these traits should also be calculated by new method for international genetic evaluation.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.8
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• pp.1066-1073
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• 2017

Objective: Growth-related traits are important economic traits in the swine industry. However, the genetic mechanism of growth-related traits is little known. The aim of this study was to screen the candidate genes and molecular markers associated with body dimension and body weight traits in pigs. Methods: A genome-wide association study (GWAS) on body dimension and body weight traits was performed in a White $Duroc{\times}Erhualian$ $F_2$ intercross by the illumina PorcineSNP60K Beadchip. A mixed linear model was used to assess the association between single nucleotide polymorphisms (SNPs) and the phenotypes. Results: In total, 611 and 79 SNPs were identified significantly associated with body dimension traits and body weight respectively. All SNPs but 62 were located into 23 genomic regions (quantitative trait loci, QTLs) on 14 autosomal and X chromosomes in Sus scrofa Build 10.2 assembly. Out of the 23 QTLs with the suggestive significance level ($5{\times}10^{-4}$), three QTLs exceeded the genome-wide significance threshold ($1.15{\times}10^{-6}$). Except the one on Sus scrofa chromosome (SSC) 7 which was reported previously all the QTLs are novel. In addition, we identified 5 promising candidate genes, including cell division cycle 7 for abdominal circumference, pleiomorphic adenoma gene 1 and neuropeptides B/W receptor 1 for both body weight and cannon bone circumference on SSC4, phosphoenolpyruvate carboxykinase 1, and bone morphogenetic protein 7 for hip circumference on SSC17. Conclusion: The results have not only demonstrated a number of potential genes/loci associated with the growth-related traits in pigs, but also laid a foundation for studying the genes' role and further identifying causative variants underlying these loci.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.10
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• pp.1341-1347
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• 2011

The objective of this study was to investigate polymorphisms of keratin-associated protein 8.1 (KAP8.1) gene and its effect on fibre traits of Chinese Inner Mongolian Cashmere goats. The fibre traits data investigated were cashmere fibre diameter, combed cashmere weight, cashmere fibre length and guard hair length. Five hundred and forty animals were used to detect polymorphisms in the complete coding sequence of the hircine KAP8.1 gene by means of PCR-SSCP. The results identified six genotypes, AA, BB, CC, AB, AC and BC, coded for by three different alleles A, B and C. Two SNPs in the coding region were confirmed by sequencing, which were T113G and G116C respectively. The relationships between the genotypes and cashmere fibre diameter, combed cashmere weight, cashmere fibre length and guard hair length were analyzed. There were significant differences between the associations of the different genotypes with cashmere weight (p<0.01), cashmere length (p<0.05) and hair length (p<0.01). Cashmere fibre diameter was the only trait that was not associated with the genotypes. The animals of genotype AB and BB had the higher cashmere weight compared with the genotype AA. By further analysis, it appeared that the KAP8.1 genotype effects on fibre traits may be due to a mutation at the 113 locus. These results suggested that polymorphisms in the hircine KAP8.1 gene might be a potential molecular marker for cashmere weight in Cashmere goats.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.12
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• pp.1689-1695
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• 2017

Objective: The cytokine inducible SH2-containing protein (CISH), which might play a role in porcine intestine immune responses, was one of the promising candidate genes for piglet anti-disease traits. An experiment was conducted to characterize the porcine CISH (pCISH) gene and to evaluate its genetic effects on pig anti-disease breeding. Methods: Both reverse transcription polymerase chain reaction (RT-PCR) and PCR were performed to obtain the sequence of pCISH gene. A pEGFP-C1-CISH vector was constructed and transfected into PK-15 cells to analysis the distribution of pCISH. The sequences of individuals were compared with each other to find the polymorphisms in pCISH gene. The association analysis was performed in Min pigs and Landrace pigs to evaluate the genetic effects on piglet diarrhea traits. Results: In the present research, the coding sequence and genomic sequence of pCISH gene was obtained. Porcine CISH was mainly localized in cytoplasm. TaqI and HaeIII PCR restriction fragment length polymorphism (RFLP) assays were established to detect single nucleotide polymorphisms (SNPs); A-1575G in promoter region and A2497C in Intron1, respectively. Association studies indicated that SNP A-1575G was significantly associated with diarrhea index of Min piglets (p<0.05) and SNP A2497C was significantly associated with the diarrhea trait of both Min pig and Landrace piglets (p<0.05). Conclusion: This study suggested that the pCISH gene might be a novel candidate gene for pig anti-disease traits, and further studies are needed to confirm the results of this preliminary research.

• The Plant Pathology Journal
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• v.29 no.3
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• pp.223-233
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• 2013

Rice stripe virus (RSV) is one of the most destructive viruses of rice, and greatly reduces rice production in China, Japan, and Korea, where mostly japonica cultivars of rice are grown. RSV is transmitted by the small brown plant-hopper (SBPH) in a persistent and circulative-propagative manner. Several methods have been developed for detection of RSV, which is composed of four single-stranded RNAs that encode seven proteins. Genome sequence data and comparative phylogenetic analysis have been used to identify the origin and diversity of RSV isolates. Several rice varieties resistant to RSV have been selected and QTL analysis and fine mapping have been intensively performed to map RSV resistance loci or genes. RSV genes have been used to generate several genetically modified transgenic rice plants with RSV resistance. Recently, genome-wide transcriptome analyses and deep sequencing have been used to identify mRNAs and small RNAs involved in RSV infection; several rice host factors that interact with RSV proteins have also been identified. In this article, we review the current statues of RSV research and propose integrated approaches for the study of interactions among RSV, rice, and the SBPH.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.1
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• pp.36-42
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• 2016

Milk-related traits (milk yield, fat and protein) have been crucial to selection of Holstein. It is essential to find the current selection trends of Holstein. Despite this, uncovering the current trends of selection have been ignored in previous studies. We suggest a new formula to detect the current selection trends based on single nucleotide polymorphisms (SNP). This suggestion is based on the best linear unbiased prediction (BLUP) and the Fisher's fundamental theorem of natural selection both of which are trait-dependent. Fisher's theorem links the additive genetic variance to the selection coefficient. For Holstein milk production traits, we estimated the additive genetic variance using SNP effect from BLUP and selection coefficients based on genetic variance to search highly selective SNPs. Through these processes, we identified significantly selective SNPs. The number of genes containing highly selective SNPs with p-value <0.01 (nearly top 1% SNPs) in all traits and p-value <0.001 (nearly top 0.1%) in any traits was 14. They are phosphodiesterase 4B (PDE4B), serine/threonine kinase 40 (STK40), collagen, type XI, alpha 1 (COL11A1), ephrin-A1 (EFNA1), netrin 4 (NTN4), neuron specific gene family member 1 (NSG1), estrogen receptor 1 (ESR1), neurexin 3 (NRXN3), spectrin, beta, non-erythrocytic 1 (SPTBN1), ADP-ribosylation factor interacting protein 1 (ARFIP1), mutL homolog 1 (MLH1), transmembrane channel-like 7 (TMC7), carboxypeptidase X, member 2 (CPXM2) and ADAM metallopeptidase domain 12 (ADAM12). These genes may be important for future artificial selection trends. Also, we found that the SNP effect predicted from BLUP was the key factor to determine the expected current selection coefficient of SNP. Under Hardy-Weinberg equilibrium of SNP markers in current generation, the selection coefficient is equivalent to $2^*SNP$ effect.