Bioinformatics research using next generation sequencing data to compare genomic features between populations and a review of future genetic resources

Next generation sequencing;genetic comparison;population analysis;genetic resource;African cattle;차세대 염기서열 해독;유전적 비교;집단 분석;유전 자원;아프리카 소;574

자연과학대학 협동과정 생물정보학전공 ;

University:서울대학교 대학원

关键词: Next generation sequencing;    genetic comparison;    population analysis;    genetic resource;    African cattle;    차세대 염기서열 해독;    유전적 비교;    집단 분석;    유전 자원;    아프리카 소;    574;   

Others  :  http://s-space.snu.ac.kr/bitstream/10371/131174/1/000000020954.pdf

美国|英语

来源: Seoul National University Open Repository

【 摘 要 】

Genome is a blueprint of organism, so there have been a lot of studies trying to describe phenomenon of life through genome analyses. Given recent development of Next Generation Sequencing (NGS) and reduction of sequencing cost, analyses of whole genome sequencing data between populations became financially possible in individual labs. From gathered genomic variations of individuals, genomic features of each population can be described and compared, and moreover, phenotypic differences between populations can be explained in a view of DNA sequences. Livestock of which characteristics are various have been domesticated for a long time, and signatures of domestication remains on their genome sequences. Thus, those animals have been considered to be good research models and researched by many researchers. In Chapter 1, I simply summarized and reviewed history of DNA sequencing and NGS technologies. Also, methods for comparative analyses between populations especially which are used in this study such as methods to define positive selection regions were briefly reviewed.In Chapter 2, I analyzed two of goat populations to compare their genomic contents and understand distinct genetic features of patterns of selection in the populations using NGS whole genome sequence data (Illumina flatform) from 15 Korean native goats and 11 crossbred goats. Because goats are the closest animal to cattle, I researched as preceding analyses for the research of African cattle project which I will cover on Chapter 3. I used GATK software to perform variant calling, and the called SNPs data was used in this study. From the identified variants in two goat populations, I discovered that Korean native goats evidently have lower nucleotide diversity than crossbred goats. Also, I revealed that ancestry of their common ancestor still hold a large majority in both of populations using STRUCTURE although they were clearly distinguished. The results of genetic structure of goat populations also supported the information of population which was already known. Through analysis using XP-EHH statistics, which is one of the methods to define positive selection regions, 6 candidate genes including predicted genes which show signatures of strong positive selection were identified. I also performed gene ontology term analysis, and DAVID tool was used in this study. GO term analyses with genes in highly variable regions showed the potential chances of gaining variations in genes involved with olfactory and neurological systems, but in practice, GO term analyses with non-synonymous SNP revealed that genes involved with olfactory and immune systems show differences between Korean native goat and crossbred goat populations.In Chapter 3, I reviewed African indigenous cattle as future genetic resources. African indigenous cattle show varieties of characteristics with the result that they have been adapted to various and harsh environmental conditions. I investigated phenotypic and genetic features of African indigenous cattle and described the necessities of research on African indigenous cattle as future genetics resources. I also investigated previous researches on African indigenous cattle and briefly describe expected goals of researches on African cattle in the future.