• Asian-Australasian Journal of Animal Sciences
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• 제25권5호
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• pp.613-620
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• 2012

Marbling from intramuscular fat is an important trait of meat quality and has an economic benefit for the beef industry. Quantitative trait loci (QTL) fine mapping was performed to identify the marbling trait in 266 Hanwoo steers using a 10K single nucleotide polymorphism panel with the combined linkage and linkage disequilibrium method. As a result, we found nine putative QTL regions for marbling: three on BTA6, two on BTA17, two on BTA22, and two on BTA29. We detected candidate genes for marbling within 1 cM of either side of the putative QTL regions. Additionally, to understand the functions of these candidate genes at the molecular level, we conducted a functional categorization using gene ontology and pathway analyses for those genes involved in lipid metabolism or fat deposition. In these putative QTL regions, we found 95 candidate genes for marbling. Using these candidate genes, we found five genes that had a direct interaction with the candidate genes. We also found SCARB1 as a putative candidate gene for marbling that involves fat deposition related to cholesterol transport.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.169-182
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• 2007

Receive operating characteristic (ROC) approach can be employed to rank candidate genes from a microarray experiment, in particular, for the biomarker development with the purpose of population screening of a cancer. In the cancer microarray experiment based on n patients the researcher often wants to compare the tumor tissue with the normal tissue within the same individual using a common reference RNA. Ideally, this experiment produces n pairs of microarray data. However, it is often the case that there are missing values either in the normal or tumor tissue data. Practically, we have $n_1$ pairs of complete observations, $n_2$ "normal only" and $n_3$ "tumor only" data for the microarray. We refer to this data set as a mixed data set. We develop a ROC approach on the mixed data set to rank candidate genes for the biomarker development for the colorectal cancer screening. It turns out that the correlation between two ranks in terms of ROC and t statistics based on the top 50 genes of ROC rank is less than 0.6. This result indicates that employing a right approach of ranking candidate genes for the biomarker development is important for the allocation of resources.

• Asian-Australasian Journal of Animal Sciences
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• 제18권8호
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• pp.1061-1065
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• 2005

Growth rate is one of the economically important quantitative traits that affect carcass quantity in beef cattle. Two genes, bovine insulin-like growth factor I (IGF-I) and myogenic factor 5 (MYF5), were chosen as candidate genes for growth traits due to their important role in growth and development of mammals. The objectives of this study were to determine gene-specific single nucleotide polymorphism (SNP) markers of the IGF-I and MYF5 positional candidate genes and to investigate their associations with growth traits in Korean cattle. Genotyping of the SNP markers in these candidate genes was carried out using the single strand conformation polymorphism (SSCP) analysis. The frequencies of A and B alleles were 0.72 and 0.28 for IGF-I gene and 0.39 and 0.61 for MYF5 gene, respectively, in Korean cattle population examined. The gene-specific SNP marker association analysis indicated that the SNP genotype in IGF-I gene showed a significant association (p<0.05) with weight at 3 months (W3), and cows with AB genotype had higher W3 than BB genotype cows. The SNP genotype of MYF5 gene was found to have a significant effect (p<0.05) on the weight at 12 months (W12) and average daily gain (ADG), and cows with BB and AB genotypes had higher W12 and ADG compared with cows with AA genotype, respectively. However, no significant association between the SNP genotypes and any other growth traits was detected. The gene-specific SNP markers in the IGF-I and MYF5 candidate genes may be useful for selection on growth traits in Korean cattle.

• Journal of Animal Science and Technology
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• 제47권3호
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• pp.325-340
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• 2005

Great success has been being achieved in identification and utilization of candidate genes affecting economically important as well as disease related traits in animals for the past two decades. This article reviews the current status of candidate genes in animals, with particular emphasis on the disease causing genes in livestock. Two different types of phenotypes, monogenic and polygenic, are also described. Finally, commercialized animal DNA markers, which can be used for the molecular breeding in near future, are discussed.

• Genomics & Informatics
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• 제6권1호
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• pp.32-35
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• 2008

Little evidence supports the existence of imprinted genes in chicken. Imprinted genes are thought to be intimately connected with the acquisition of parental resources in mammals; thus, the predicted lack of this type of gene in chicken is not surprising, given that they leave their offspring to their own heritance after conception. In this study, we identified several imprinted genes and their orthologs in human, mouse, and zebrafish, including 30 previously identified human and mouse imprinted genes. Next, using the HomoloGene database, we identified six orthologous genes in human, mouse, and chicken; however, no orthologs were identified for SLC22A18, and mouse Ppp1r9a was not included in the HomoloGene database. Thus, from our analysis, four candidate chicken imprinted genes (IGF2, UBE3A, PHLDA2, and GRB10) were identified. To expand our analysis, zebrafish was included, but no probe ID for UBE3A exists in this species. Thus, ultimately, three candidate imprinted genes (IGF2, PHLDA2, and GRB10) in chicken were identified. GRB10 was not significant in chicken and zebrafish based on the Wilcoxon-Mann-Whitney test, whereas a weak correlation between PHLDA2 in chicken and human was identified from the Spearman's rank correlation coefficient. Significant associations between human, mouse, chicken, and zebrafish were found for IGF2 and GRB10 using the Friedman's test. Based on our results, IGF2, PHLDA2, and GRB10 are candidate imprinted genes in chicken. Importantly, the strongest candidate was PHLDA2.

• Genomics & Informatics
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• 제6권3호
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• pp.153-156
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• 2008

Complex diseases such as stroke and cancer have two or more genetic loci and are affected by environmental factors that contribute to the diseases. Due to the complex characteristics of these diseases, identifying candidate genes requires a system-level analysis of the following: gene ontology, pathway, and interactions. A database and user interface, termed StrokeBase, was developed; StrokeBase provides queries that search for pathways, candidate genes, candidate SNPs, and gene networks. The database was developed by using in silico data mining of HGNC, ENSEMBL, STRING, RefSeq, UCSC, GO, HPRD, KEGG, GAD, and OMIM. Forty candidate genes that are associated with cerebrovascular disease were selected by human experts and public databases. The networked cerebrovascular disease gene maps also were developed; these maps describe genegene interactions and biological pathways. We identified 1127 genes, related indirectly to cerebrovascular disease but directly to the etiology of cerebrovascular disease. We found that a protein-protein interaction (PPI) network that was associated with cerebrovascular disease follows the power-law degree distribution that is evident in other biological networks. Not only was in silico data mining utilized, but also 250K Affymetrix SNP chips were utilized in the 320 control/disease association study to generate associated markers that were pertinent to the cerebrovascular disease as a genome-wide search. The associated genes and the genes that were retrieved from the in silico data mining system were compared and analyzed. We developed a well-curated cerebrovascular disease-associated gene network and provided bioinformatic resources to cerebrovascular disease researchers. This cerebrovascular disease network can be used as a frame of systematic genomic research, applicable to other complex diseases. Therefore, the ongoing database efficiently supports medical and genetic research in order to overcome cerebrovascular disease.

• Journal of Animal Science and Technology
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• 제62권3호
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• pp.293-305
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• 2020

The difference in the breeding programs and population history may have diversely shaped the genomes of Korean native cattle breeds. In the absence of phenotypic data, comparisons of breeds that have been subjected to different selective pressures can aid to identify genomic regions and genes controlling qualitative and complex traits. In this study to decipher genetic variation and identify evidence of divergent selection, 3 Korean cattle breeds were genotyped using the recently developed high-density GeneSeek Genomic Profiler F250 (GGP-F250) array. The three Korean cattle breeds clustered according to their coat color phenotypes and breeding programs. The Heugu breed reliably showed smaller effective population size at all generations considered. Across the autosomal chromosomes, 113 and 83 annotated genes were identified from Hanwoo-Chikso and Hanwoo-Heugu comparisons, respectively of which 16 genes were shared between the two pairwise comparisons. The most important signals of selection were detected on bovine chromosomes 14 (24.39-25.13 Mb) and 18 (13.34-15.07 Mb), containing genes related to body size, and coat color (XKR4, LYN, PLAG1, SDR16C5, TMEM68, CDH15, MC1R, and GALNS). Some of the candidate genes are also associated with meat quality traits (ACSF3, EIF2B1, BANP, APCDD1, and GALM) and harbor quantitative trait locus (QTL) for beef production traits. Further functional analysis revealed that the candidate genes (DBI, ACSF3, HINT2, GBA2, AGPAT5, SCAP, ELP6, APOB, and RBL1) were involved in gene ontology (GO) terms relevant to meat quality including fatty acid oxidation, biosynthesis, and lipid storage. Candidate genes previously known to affect beef production and quality traits could be used in the beef cattle selection strategies.

• Asian-Australasian Journal of Animal Sciences
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• 제32권8호
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• pp.1084-1094
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• 2019

Objective: The aim of this study was to select the candidate genes affecting meat quality and preliminarily explore the related molecular mechanisms in the Mashen pig. Methods: The present study explored genetic factors affecting meat quality in the Mashen pig using RNA sequencing (RNA-Seq). We sequenced the transcriptomes of 180-day-old Mashen and Large White pigs using longissimus dorsi to select differentially expressed genes (DEGs). Results: The results indicated that a total of 425 genes were differentially expressed between Mashen and Large White pigs. A gene ontology enrichment analysis revealed that DEGs were mainly enriched for biological processes associated with metabolism and muscle development, while a Kyoto encyclopedia of genes and genomes analysis showed that DEGs mainly participated in signaling pathways associated with amino acid metabolism, fatty acid metabolism, and skeletal muscle differentiation. A MCODE analysis of the protein-protein interaction network indicated that the four identified subsets of genes were mainly associated with translational initiation, skeletal muscle differentiation, amino acid metabolism, and oxidative phosphorylation pathways. Conclusion: Based on the analysis results, we selected glutamic-oxaloacetic transaminase 1, malate dehydrogenase 1, pyruvate dehydrogenase 1, pyruvate dehydrogenase kinase 4, and activator protein-1 as candidate genes affecting meat quality in pigs. A discussion of the related molecular mechanisms is provided to offer a theoretical basis for future studies on the improvement of meat quality in pigs.

• Journal of Animal Science and Technology
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• 제65권2호
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• pp.311-323
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• 2023

Beef consumers valued meat quality traits such as texture, tenderness, juiciness, flavor, and meat color that determining consumers' purchasing decision. Most research on meat quality has focused on marbling, a key characteristic related to meat eating quality. However, other important traits such as meat texture, tenderness, and color have not much studied in cattle. Among these traits, meat tenderness and texture of cattle are among the most important factors affecting quality evaluation of consumers. Collagen is the main component of connective tissues.It greatly affects meat tenderness. The objective of this study was to determine significant variants and candidate genes associated with collagen contents trait (total collagen) through genome-wide association studies (GWAS). Phenotypic and genomic data from 135 Hanwoo were used. The BLUPF90 family program and GRAMMAR method for GWAS were applied in this study. A total of 73 potential single nucleotide polymorphisms (SNPs) showed significant associations with collagen content. They were located in or near 108 candidate genes. TMEM135 and ME3 genes were identified to have the most significant SNPs associated with collagen contents trait. Data indicated that these genes were related to collagen. Biological processes and pathways for the prediction of biological functions of candidate genes were confirmed. We found that candidate genes were involved in positive regulation of CREB transcription factor activity and actin cytoskeleton related to tenderness and texture of beef. Three genes (CRTC3, MYO1C and MYLK4) belonging to these biological functions were related to tenderness. These results provide a basis for improving genomic characteristics of Hanwoo for the production of tender beef. Furthermore, they could be used they could be used as an index to select desired traits for consumers.

• BMB Reports
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• 제40권2호
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• pp.226-231
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• 2007

Housekeeping genes are widely used as internal controls in a variety of study types, including real time RT-PCR, microarrays, Northern analysis and RNase protection assays. However, even commonly used housekeeping genes may vary in stability depending on the cell type or disease being studied. Thus, it is necessary to identify additional housekeeping-type genes that show sample-independent stability. Here, we used statistical analysis to examine a large human microarray database, seeking genes that were stably expressed in various tissues, disease states and cell lines. We further selected genes that were expressed at different levels, because reference and target genes should be present in similar copy numbers to achieve reliable quantitative results. Real time RT-PCR amplification of three newly identified reference genes, CGI-119, CTBP1 and GOLGAl, alongside three well-known housekeeping genes, B2M, GAPD, and TUBB, confirmed that the newly identified genes were more stably expressed in individual samples with similar ranges. These results collectively suggest that statistical analysis of microarray data can be used to identify new candidate housekeeping genes showing consistent expression across tissues and diseases. Our analysis identified three novel candidate housekeeping genes (CGI-119, GOLGA1, and CTBP1) that could prove useful for normalization across a variety of RNA-based techniques.