Understanding the genome of living organism based on the second generation sequencing

Abstract

These studies are mainly about the rebuilding genome sequence of living organism using de novo assembly based on the second generation sequencing technologies and understanding the gene level features of organisms. Even though the next generation sequencing, especially the second generation sequencing, make the genome project can be conducted in reasonable price, assembling the short read from the second generation sequencing is challenging. Various programs which have its unique characteristics are available but one program or pipeline cannot be the best choice at any times. Therefore, researchers who want to rebuild the genome sequence using de novo assembly have to choose the best combination of programs and pipeline for specific data. In chapter 2, I make the efficient combination of programs for the de novo assembly of microbes and the finished level genome assembly of the probiotic candidates had been conducted using short reads from two sequencing technologies. Based on the result of assembly, I found the potential risk as a useful probiotic strain. In chapter 3, minke whale genome assembly had been conducted using low coverage re-sequencing data. I found the efficient genome assembly pipeline using various open source programs which showed better performance than the assembly result of the expensive commercial program. And contig extension and bridging were conducted to combine the result of assembly from different samples. In chapter 4, assembly of unaligned reads from short read alignment to the reference genome was conducted to identify the unique sequence and gene contents of Korean Native Chicken (KNC) samples. Based on the unaligned reads assembly and gene prediction, KNC specific genes and sequences were identified for further analysis. Through these studies, I trained making some efficient genome assembly pipelines suitable for specific data and learned the way to understand the characteristics of living organisms based on the assembly and gene level features.