S-Space College of Natural Sciences (자연과학대학) Program in Bioinformatics (협동과정-생물정보학전공) Theses (Master's Degree_협동과정-생물정보학전공)
Trailing genomic signature to discover substantial information in genome data using bioinformatics approaches
생물정보학적 접근방법을 이용한 유전적 표지인자 탐색과 유전체데이터의 유용한 정보 발굴
- 자연과학대학 협동과정 생물정보학전공
- Issue Date
- 서울대학교 대학원
- 학위논문 (석사)-- 서울대학교 대학원 : 협동과정 생물정보학전공, 2016. 2. 김희발.
- These studies are mainly focusing on the deciphering biologically meaningful information in genome sequences of living organisms using bioinformatics techniques.
In chapter 2, I investigate the relationship between genomic composition and Berkshire pig’s meat quality trait by scanning for signatures of positive selection in whole-genome sequencing data. Berkshire pigs are regarded as having superior meat quality compared to other breeds. As the meat production industry seeks selective breeding approaches to improve profitable traits such as meat quality, information about genetic determinants of these traits is in high demand. However, most of the studies have been performed using trained sensory panel analysis without investigating the underlying genetic factors. Results revealed several candidate genes involved in Berkshire meat quality
most of these genes are involved in lipid metabolism and intramuscular fat deposition.
In chapter 3, I construct the HGTree: database of horizontally transferred genes determined by tree reconciliation. In Bacteria and Archaea, Horizontal gene transfer (HGT) plays an important role in the acquisition of biological advantages such as virulence factor and antibiotic resistance and provides significant genetic diversity. It is important to have a well-defined database containing precise information about HGT events between Prokaryotes in order to understand prokaryotic evolution and discover genes which have led to adaptive genetic variation through HGT as opposed to processes such as mutation, natural selection, or genetic drift. The HGTree database provides putative genome-wide horizontal gene transfer information for 2,472 prokaryotic genomes by reconciling gene trees against species trees. The tree reconciliation method is considered to be a useful way to detect HGT events but has not been utilized extensively by existing databases because the method is computationally intensive and conceptually challenging. In this regard, HGTree represents a useful addition to the biological community, enabling quick and easy retrieval of information for HGT-acquired genes and better understanding of microbial taxonomy and evolution. The database is freely available and can be easily scaled and updated to keep pace with the rapid rise in genomic information.