Is APAC Edging Closer to Clinical Application of Single-cell Tech?

Asia Pacific APAC) is expected to be a major contributor to the growth of single cell technology as the market is driven by factors such as the growing demand for personalised medicine, advancements in sequencing technologies, and the increasing use of single cell analysis in drug discovery. While Japan is currently the fastest-growing country in the APAC single-cell analysis market, Singapore, China, and India are showing significant progress in adopting this technology.

- Anusha Ashwin

A single cell contains multiple omics including genome, epigenome, transcriptome, and others. The completion of the Human Genome Project in 2003 was the beginning of deciphering the biological meaning of the three billion nucleotides in the human genome. Later, a key technological milestone was the release of several massively parallel DNA sequencing (next-generation sequencing) platforms in 2005 and 2007, which allowed for generating sequencing reads of billions of base pairs in a few days at a cost of less than $1,000. Moving on, the single-cell omics sequencing research started in 2009 when the single-cell RNA sequencing (scRNA-seq) assay was described.

In recent years, more and more single-cell technologies have been developed. A vast amount of single-cell omics data has been generated by large projects globally, such as the Human Cell Atlas, the Mouse Cell Atlas, the Mouse RNA Atlas, the Mouse ATAC Atlas, and the Plant Cell Atlas. Based on these single-cell big data, thousands of bioinformatics algorithms for quality control, clustering, cell-type annotation, developmental inference, cell-cell transition, cell-cell interaction, and spatial analysis are developed. Some of the most common single-cell technology methods include Single-cell RNA sequencing (scRNA-seq); Single-cell proteomics; Single-cell epigenomics; Single-cell imaging; and Single-cell electrophysiology.

Notably, the first successful demonstration of single cell RNA sequencing was published in 2009 by a team of researchers at the University of Washington led by Dr Jay Shendure and Dr Cole Trapnell. They used a method called Smart-seq to amplify and sequence the mRNA from individual mouse blastomeres (early-stage embryonic cells) and demonstrated that the technique could be used to profile gene expression in individual cells.