Dr. Yasushi Okazaki, team leader, and Dr. Ken Yagi, deputy team leader of RIKEN Center for Integrative Medical Sciences, gave an inspiring speech about the MGI high-throughput genetic sequencer MGISEQ-2000 as the highly versatile platform to satisfy the multiple needs of RIKEN research projects.

At the Technology and Application Conference of Genomics (TACG) during ICG-13 on 25 October 2018, Dr. Yasushi Okazaki, Team Leader, and Dr. Ken Yagi, Deputy Team Leader of the RIKEN Center for Integrative Medical Sciences, presented their research using MGI’s high-throughput sequencer, MGISEQ-2000. The platform has proven highly versatile, supporting multiple large-scale genomics projects at RIKEN.

RIKEN, one of Japan’s leading national research institutes, installed its first MGISEQ-2000 in early 2018. Since then, the sequencer has been applied to international initiatives such as the Functional Annotation of Mammalian Genome (FANTOM) project and the Human Cell Atlas (HCA) project. For FANTOM, MGISEQ-2000 was used with Cap Analysis of Gene Expression (CAGE) to map transcription start sites comprehensively. In the HCA project, it enabled single-cell RNA analysis using Random Displacement Amplification Sequencing (RamDA-seq), supporting full-length total RNA sequencing at single-cell resolution.

Dr. Yagi highlighted comparative studies on whole-genome sequencing (WGS) data from human liver cancer and normal tissue using MGISEQ-2000 and Illumina HiSeq 2500. Analyses of single-nucleotide variants (SNVs) and insertion/deletion polymorphisms (INDELs) confirmed that MGISEQ-2000 delivers highly accurate and reliable results.

“As MGISEQ-2000 is both highly accurate and cost-effective, we will continue to use this instrument in our research,” said Dr. Okazaki.

About RIKEN
Founded in 1917, RIKEN is Japan’s largest comprehensive research institution, with a network of world-class centers across the country. The Center for Integrative Medical Sciences conducts cutting-edge research on human genome, immune function, and disease pathogenesis, employing multi-omics analyses across genomes, proteins, lipids, cells, tissues, and individuals using advanced computational methods.