Title Page

Contents

CHAPTER Ⅰ. Literature review 8

1.1. Introduction 8

1.2. Genomic-wide association study 11

1.3. Text-mining 12

1.4. Quantitative Trait Loci Database 14

CHAPTER Ⅱ. Validation of genome-wide association study utilized text-mining approach to detect fatty-acid related genes of Hanwoo cattle 16

2.1. Introduction 16

2.2. Materials and Methods 19

2.2.1. Animal and phenotype data 19

2.2.2. Genotyping and quality control 20

2.2.3. Text-mining and SNP extraction 21

2.2.4. Gene Ontology analysis and karyotyping 24

2.2.5. Genome-Wide Association Study using the imputed whole and text-mined SNPs 24

2.2.6. BayesR using the imputed 777K and test-mined SNPs 25

2.3. Results 26

2.3.1. Phenotype 26

2.3.2. Text-mined gene and SNP extraction 27

2.3.3. Detailed functional studies by Gene Ontology analysis used Text-mined genes 32

2.3.4. The QTL regions between cattle QTL database and text-mined-genes 37

2.3.5. Genome-wide association study using the imputed whole and text-mined SNPs 40

2.3.6. BayesR using text-mined SNPs 41

2.4. DISCUSSION 50

2.4.1. Text-mining 50

2.4.2. Genome-Wide Association Study 51

2.4.3. Limitation of Text-mining 54

2.5. Conclusions 55

REFERENCES 56

ABSTRACT 64

초록 67

Table 2.1. Fatty acids composition in Hanwoo 27

Table 2.2. Summary statistics of text-mined genes and SNP calling 28

Table 2.3. The top five significant biological processes for each trait 34

Table 2.4. Significant SNPs in genome-wide association study for myristic acid in Hanwoo cattle 45

Figure 2.1. Workflow of text-mining 23

Figure 2.2. The top 30 text-mined genes 29

Figure 2.3. The karyotype of QTL regions registered in QTLDB, text-mined region and the intersection of both regions 39

Figure 2.4. Manhattan plots with results of genome-wide association study, GWAS using text-mined SNPs and BayesR for Myristic acid 43