• Genomics & Informatics
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• 제8권3호
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• pp.150-158
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• 2010

Genome-wise association studies (GWASs) have become popular approaches to identify genetic variants associated with human biological traits. In this study, we applied Structural Equation Models (SEMs) in order to model complex relationships between genetic networks and traits as risk factors. SEMs allow us to achieve a better understanding of biological mechanisms through identifying greater numbers of genes and pathways that are associated with a set of traits and the relationship among them. For efficient SEM analysis for GWASs, we developed a procedure, comprised of four stages. In the first stage, we conducted single-SNP analysis using regression models, where age, sex, and recruited area were included as adjusting covariates. In the second stage, Fisher's combination test was conducted for each gene to detect significant genes using p-values obtained from the single-SNP analysis. In the third stage, Fisher's exact test was adopted to determine which biological pathways were enriched with significant SNPs. Finally, based on a pathway that was associated with the four traits in common, a SEM was fit to model a causal relationship among the genetic factors and traits. We applied our SEM model to GWAS data with four central obesity related traits: suprailiac and subscapular measures for upper body fat, BMI, and hypertension. Study subjects were collected from two Korean cohort regions. After quality control, 327,872 SNPs for 8842 individuals were included in the analysis. After comparing two SEMs, we concluded that suprailiac and subscapular measures may indirectly affect hypertension susceptibility by influencing BMI. In conclusion, our analysis demonstrates that SEMs provide a better understanding of biological mechanisms by identifying greater numbers of genes and pathways.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2018년도 추계학술대회
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• pp.9-12
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• 2018

China is an agricultural country. Rice, maize and soybean are major crops for national economy and people's livelihood. These three crops are also the pillar industry in northeast China, especially in Heilongjiang province.

• Genomics & Informatics
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• 제12권4호
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• pp.254-260
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• 2014

Best linear unbiased prediction (BLUP) has been used to estimate the fixed effects and random effects of complex traits. Traditionally, genomic relationship matrix-based (GRM) and random marker-based BLUP analyses are prevalent to estimate the genetic values of complex traits. We used three methods: GRM-based prediction (G-BLUP), random marker-based prediction using an identity matrix (so-called single-nucleotide polymorphism [SNP]-BLUP), and SNP-SNP variance-covariance matrix (so-called SNP-GBLUP). We used 35,675 SNPs and R package "rrBLUP" for the BLUP analysis. The SNP-SNP relationship matrix was calculated using the GRM and Sherman-Morrison-Woodbury lemma. The SNP-GBLUP result was very similar to G-BLUP in the prediction of genetic values. However, there were many discrepancies between SNP-BLUP and the other two BLUPs. SNP-GBLUP has the merit to be able to predict genetic values through SNP effects.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1618-1618
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• 2001

Predicting quality traits using near infrared (NIR) spectroscopy on whole grain samples has gained wide acceptance as a non-destructive, rapid and cost effective technique. Barley breeding programs throughout southern Australia currently use this technology as a tool for selecting malting quality lines. For the past 3 years whole grain barley calibrations have been developed at VIDA to predict malting quality traits in the early generation selections of the breeding program. More recently calibrations for whole grain malt have been developed and introduced to aid in selecting malted samples at the mid-generation stage for more complex malting quality traits. Using the same population set, barley and malt calibrations were developed to predict hot water extracts (EBC and IoB), diastatic power, free $\alpha$-amino nitrogen, soluble protein, wort $\beta$-glucan and $\beta$-glucanase. The correlation coefficients between NIR predicted values and laboratory methods for malt were all highly significant ($R^2$ > 0.84), whereas the correlation coefficients for the barley calibrations were lower ($R^2$ > 0.57) but still significant. The magnitude of the error in predicting hot water extract, diastatic power and wort $\beta$-glucan using whole grain malt was reduced by 50% when compared with predicting the same trait using whole grain barley. This can be explained by the complex nature of attempting to develop calibrations on whole grain barley utilizing malt data. During malting, the composition of barley is modified by the action of enzymes throughout the steeping and germination stages and by heating during the kilning stage. Predicting malting quality on whole grain malt is a more reliable alternative to predicting whole grain barley, although there is the added expense of micro-malting the samples. The ability to apply barley and malt calibrations to different generations is an advantage to a barley breeding program that requires thousands of samples to be assessed each year.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.207-207
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• 2022

Eating and cooking quality (ECQ) is one of the most complex quantitative traits in rice. The understanding of genetic regulation of transcript expression levels attributing to phenotypic variation in ECQ traits is limited. We integrated whole-genome resequencing, transcriptome, and phenotypic variation data from 84 Japonica accessions to build a transcriptome-wide association study (TWAS) based regulatory network. All ECQ traits showed a large phenotypic variation and significant phenotypic correlations among the traits. TWAS analysis identified a total of 285 transcripts significantly associated with six ECQ traits. Genome-wide mapping of ECQ-associated transcripts revealed 66,905 quantitative expression traits (eQTLs), including 21,747 local eQTLs, and 45,158 trans-eQTLs, regulating the expression of 43 genes. The starch synthesis-related genes (SSRGs), starch synthase IV-1 (SSIV-1), starch branching enzyme 1 (SBE1), granule-bound starch synthase 2 (GBSS2), and ADP-glucose pyrophosphorylase small subunit 2a (OsAGPS2a) were found to have eQTLs regulating the expression of ECQ associated transcripts. Further, in co-expression analysis, 130 genes produced at least one network with 22 master regulators. In addition, we developed CRISPR/Cas9-edited glbl mutant lines that confirmed the role of alpha-globulin (glbl) in starch synthesis to validate the co-expression analysis. This study provided novel insights into the genetic regulation of ECQ traits, and transcripts associated with these traits were discovered that could be used in further rice breeding.

• 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.

• Genomics & Informatics
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• 제13권4호
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• pp.146-151
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• 2015

Previous studies in Holstein have shown 35% to 51.8% heritability in milk production traits, such as milk yield, fat, and protein, using pedigree data. Other studies in complex human traits could be captured by common single-nucleotide polymorphisms (SNPs), and their genetic variations, attributed to chromosomes, are in proportion to their length. Using genome-wide estimation and partitioning approaches, we analyzed three quantitative Holstein traits relevant to milk production in Korean Holstein data harvested from 462 individuals genotyped for 54,609 SNPs. For all three traits (milk yield, fat, and protein), we estimated a nominally significant (p = 0.1) proportion of variance explained by all SNPs on the Illumina BovineSNP50 Beadchip ($h^2_G$). These common SNPs explained approximately most of the narrow-sense heritability. Longer genomic regions tended to provide more phenotypic variation information, with a correlation of 0.46~0.53 between the estimate of variance explained by individual chromosomes and their physical length. These results suggested that polygenicity was ubiquitous for Holstein milk production traits. These results will expand our knowledge on recent animal breeding, such as genomic selection in Holstein.

• Asian-Australasian Journal of Animal Sciences
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• 제22권1호
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• pp.124-130
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• 2009

Estimating genetic interaction effects in animal genomics would be one of the most challenging studies because the phenotypic variation for economically important traits might be largely explained by interaction effects among multiple nucleotide sequence variants under various environmental exposures. Genetic improvement of economic animals would be expected by understanding multi-locus genetic interaction effects associated with economic traits. Most analyses in animal breeding and genetics, however, have excluded the possibility of genetic interaction effects in their analytical models. This review discusses a historical estimation of the genetic interaction and difficulties in analyzing the interaction effects. Furthermore, two recently developed methods for assessing genetic interactions are introduced to animal genomics. One is the restricted partition method, as a nonparametric grouping-based approach, that iteratively utilizes grouping of genotypes with the smallest difference into a new group, and the other is the Bayesian method that draws inferences about the genetic interaction effects based on their marginal posterior distributions and attains the marginalization of the joint posterior distribution through Gibbs sampling as a Markov chain Monte Carlo. Further developing appropriate and efficient methods for assessing genetic interactions would be urgent to achieve accurate understanding of genetic architecture for complex traits of economic animals.

• Asian-Australasian Journal of Animal Sciences
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• 제31권10호
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• pp.1558-1564
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• 2018

Objective: We report monitoring conservation effect for a Chinese indigenous chicken (Langshan) breed using major histocompatibility complex (MHC) and DNA barcords. Methods: The full length of MHC B-G gene and mitochondrial cytochrome oxidase I (COI) gene in generations 0, 5, 10, 15, 16, and 17 was measured using re-sequencing and sequencing procedures, respectively. Results: There were 292 single nucleotide polymorphisms of MHC B-G gene identified in six generations. Heterozygosity (He) and polymorphic information content (PIC) of MHC B-G gene in generations 10, 15, 16, and 17 remained stable. He and PIC of MHC B-G gene were different in six generations, with G10, G15, G16, G17 >G5>G0 (p<0.05). For the COI gene, there were five haplotypes in generations 0, 5, 10, 15, 16, and 17. Where Hap2 and Hap4 were the shared haplotypes, 164 individuals shared Hap2 haplotypes, while Hap1 and Hap3 were the shared haplotypes in generations 0 and 5 and Hap5 was a shared haplotype in generations 10, 15, 16, and 17. The sequence of COI gene in 6 generations was tested by Tajima's and D value, and the results were not significant, which were consistent with neutral mutation. There were no differences in generations 10, 15, 16, and 17for measured phenotypic traits. In other generations, for annual egg production, with G5, G10, G15, G16, G17>G0 (p<0.05). For age at the first egg and age at sexual maturity, with G10, G15, G16, G17>G5>G0 (p<0.05). Conclusion: Combined with the results of COI gene DNA barcodes, MHC B-G gene, and phenotypic traits we can see that genetic diversity remained stable from generations 10 to 17 and the equimultiple random matching pedigrees conservation population conservation effect of Langshan chicken was effective as measured by these criteria.

• 한국작물학회지
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• 제46권2호
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• pp.112-120
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• 2001

Genetic diversity of 47 East-Asian vegetable soybean was characterized by means of agro-morphological traits and RAPD markers. A field trial was conducted to evaluate 14 agro-morphological traits. To study RAPD-based DNA analysis, a total of sixty 10-mer random primers were screened. Of these, 23 polymorphic markers in 16 varieties used for screening. Among 207 markers amplified, 48 were polymorphic for at least one pairwise comparison within the 47 varieties. A higher differentiation level between varieties was observed by using RAPD markers compared to morphological markers. Correspondence analysis using both types of marker showed that RAPD data could fully discriminate between all varieties, whereas morphological markers could not achieve a complete discrimination. Genetic distances between the varieties were estimated from simple matching coefficients, ranged from 0.0 to 0.640 with an average of 0.295$\pm$0.131 for morphological traits and 0.042 to 0.625 with an average of 0.336$\pm$0.099 for RAPD data, respectively. Cluster analysis based on genetic dissimilarity of these varieties gave rise to 4 distinct groups. The clustering results based on RAPDs did not match with those based on morphological traits. Geographical distribution of most varieties in each of the groups were not well defined. The results suggested that the level of genetic diversity within this group of East-Asian vegetable soybean varieties was sufficient for a breeding program and can be used to establish genetic relationships among them with unknown or unrelated pedigrees.