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tlight Projects亮
點
計
畫 A Reliable Gap-Filled Strategy for
Non-Reference Chromosome-Level Assembly:
Applications to Human Precise Medicine and Aquaculture Breeding
Principal Investigators: Dr. Chun-Yen Lin
Project Period: 2018/1~2021/12
Rapid progress in next-generation sequencing (NGS) not fully utilize all of the information available from raw
and third-generation single-molecule sequencing (TGS) sequences. Emerging sequencing technologies such as
technologies has moved biomedical research into the Hi-C (chromosome conformation capture) and Bionano
era of big data. Big data has rendered sequencing-based (optical genome mapping technology) are prompting
tasks―including bioinformatics analyses, data statistics us to integrate all available sequencing approaches to
and visualization, and data transfer and storage―more characterize genomes more comprehensively than ever.
challenging than ever, yet these issues have inspired new
research avenues in bioinformatics and biomedicine. In We have generated and collected a considerable array
particular, de novo genome assembly of human and non- of sequencing data, including NGS reads, linked reads,
model organisms for personalized medicine and genome TGS reads, and Bionano optical mapping outputs. We are
breeding are helping to analyze disease mechanisms and starting to develop a new hybrid and spiral approach to
deciphering the secrets of the genome. assess this data by integrating gap-closing and sca olding
algorithms using local de novo assembly of link reads (10x
However, methods and software for dealing with hybrid genomics). This approach has improved the draft genome
genome assembly of NGS linked-read (10x Genomics) assemblies of important aquacultural species (i.e., Japanese
and TGS long-read data are currently limited, so results eel, Taiwan Tilapia, Giant Grouper) (Figure 1), both in terms
are rarely satisfactory. However, the existing tools do of contiguity and completeness.
Figure 1 : Our novel strategy to analyzing new sequencing technology outputs signi cantly improves the
quality and extent of the Japanese eel genome assembly.
20
點
計
畫 A Reliable Gap-Filled Strategy for
Non-Reference Chromosome-Level Assembly:
Applications to Human Precise Medicine and Aquaculture Breeding
Principal Investigators: Dr. Chun-Yen Lin
Project Period: 2018/1~2021/12
Rapid progress in next-generation sequencing (NGS) not fully utilize all of the information available from raw
and third-generation single-molecule sequencing (TGS) sequences. Emerging sequencing technologies such as
technologies has moved biomedical research into the Hi-C (chromosome conformation capture) and Bionano
era of big data. Big data has rendered sequencing-based (optical genome mapping technology) are prompting
tasks―including bioinformatics analyses, data statistics us to integrate all available sequencing approaches to
and visualization, and data transfer and storage―more characterize genomes more comprehensively than ever.
challenging than ever, yet these issues have inspired new
research avenues in bioinformatics and biomedicine. In We have generated and collected a considerable array
particular, de novo genome assembly of human and non- of sequencing data, including NGS reads, linked reads,
model organisms for personalized medicine and genome TGS reads, and Bionano optical mapping outputs. We are
breeding are helping to analyze disease mechanisms and starting to develop a new hybrid and spiral approach to
deciphering the secrets of the genome. assess this data by integrating gap-closing and sca olding
algorithms using local de novo assembly of link reads (10x
However, methods and software for dealing with hybrid genomics). This approach has improved the draft genome
genome assembly of NGS linked-read (10x Genomics) assemblies of important aquacultural species (i.e., Japanese
and TGS long-read data are currently limited, so results eel, Taiwan Tilapia, Giant Grouper) (Figure 1), both in terms
are rarely satisfactory. However, the existing tools do of contiguity and completeness.
Figure 1 : Our novel strategy to analyzing new sequencing technology outputs signi cantly improves the
quality and extent of the Japanese eel genome assembly.
20
