Essentiality of Single-cell Genomics Technology

Single-cell sequencing techniques have innovated the current understanding of human diseases.

FREMONT, CA: In the past few years, molecular and cellular technologies have emerged to offer rise to the era of single-cell genomics, which enables the simultaneous measurement of genes in thousands of ‘single’ cells from a single specimen. Innovations in microfluidic and molecular cloning technologies have transformed the understanding of complex biological operations by enhancing resolution to a single-cell level. Single-cell sequencing technology has emerged over time, from processing dozens of cells to millions of cells. New methods to well-established models are being found at the single-cell level in medical sciences, and rare cell types are being reported, one after another.

Technical advancements in single-cell analyses continue to enhance the throughput and analytical dimensions at the spatial and multi-omics levels. G&T-seq and SIDR-seq represent ways for analyzing a single-cell genome and transcriptome in the same cell. CITE-seq can couple protein and transcriptome measurements into a single readout per cell. Advancements in single-cell multi-omics analysis techniques allow people to understand genetic regulation in response to several physiological and

pathological conditions. Single-cell multi-omics analysis at the chromatin, DNA methylation, and transcriptome levels during mouse embryogenesis has offered insights into epigenetic regulation before cell fate decisions.

Powered by single-cell genome analysis techniques, firms can correctly identify cell types, which is vital in developmental biology and cell therapy. The description of cell types will be replaced by cell typing powered by biomarkers and molecular profiles. Recent innovations in single-cell RNA sequencing and spatial transcriptome analyses have massively transformed the understanding of cell types. Several studies employ single-cell sequencing technologies in clinical samples and preclinical models to investigate several pathologic conditions.

Contemporary studies leveraging single-cell sequencing data revealed its versatility concerning clinical perspectives, such as describing tumor microenvironment landscapes, suggesting treatment response, discovering novel biomarkers, disease subcategorization or prognostication, monitoring residual illness after initial treatment, and deciphering the mechanisms of disease initiation and progression.