Development Of Long-Read Sequencing Methods Leveraging Target Enrichment
Long-read sequencing technologies have enabled the sequencing of DNA fragments exceeding 100 kb, significantly advancing the analysis of highly repetitive genomic regions and enabling accurate sequencing of full-length mRNA transcripts—applications that remain challenging for short-read sequencing platforms.
At the same time, hybridization-based target enrichment using complementary probes has proven to be a highly effective strategy for achieving high-depth sequencing of specific genomic regions while reducing overall sequencing costs.
In this webinar, Dr. Masahide Seki will introduce newly developed long-read sequencing methods leveraging target enrichment, with a focus on advanced workflows for long-read DNA methylation analysis and full-length cDNA sequencing. These methods are designed to improve data quality, enhance sequencing efficiency, and expand the range of biological applications accessible through long-read technologies.
What You Will Learn:
- Recent advances in long-read sequencing and remaining technical challenges
- Principles and advantages of target enrichment for long-read applications
- Development of long-read–compatible DNA methylation analysis methods
- Target enrichment strategies for full-length cDNA sequencing
- Applications in genomics, epigenomics, and transcriptome research
Who Should Attend:
- Researchers using or evaluating long-read sequencing technologies
- Scientists studying DNA methylation and epigenetic regulation
- Transcriptomics researchers requiring full-length isoform information
- Core facility managers and sequencing specialists
- Bioinformatics and genomics platform teams
Presenter: Dr. Masahide Seki (Project Associate Professor, The University of Tokyo, Japan)
Dr. Seki obtained his Ph.D. from the Graduate School of Frontier Sciences, The University of Tokyo, where he researched stem cells using next-generation sequencing in the laboratory of Professors Sumio Sugano and Yutaka Suzuki. He subsequently served as a Project Researcher and Project Assistant Professor in Prof. Yutaka Suzuki's laboratory, contributing to the Genome Support and Advanced Genome Support projects. Currently, as a Project Associate Professor, he is contributing to the Data Science Training and Education Program for Life Science (DSTEP) while developing advanced sequencing methodologies and conducting applied research on diverse biological systems, such as cancer, using state-of-the-art genomic analysis technologies.
