The precision gene editing enabled by the use of CRISPR (clustered regularly interspaced short palindromic repeats) technology has great potential for use in life science and biomedicine. Typically, a CRISPR cell engineering workflow involves the transfection of target cells with plasmid vectors containing both the CRISPR-Cas9 gene editing construct and a fluorescent reporter (this enables successfully transfected cells to be easily identified). The next step involves the isolation of edited cells for single cell cloning and clonal expansion. There are two techniques that have traditionally been used for single cell isolation, both of which have certain drawbacks.
Rapid Single Cell Isolation
Bio-Techne's single cell sorters are the simplest and fastest way to identify and isolate target CRISPR-Cas9 gene-edited single cells for your cell engineering workflow. And it's all achieved seamlessly, in one step.
Highly Efficient Single Cell Dispensing
Cells are dispensed 1 cell/well at high efficiency into 96 or 384 well plates. The image [right] shows that Bio-Techne instruments are highly efficient and consistent at dispensing single cells (80-90% with mammalian cells) compared to manual pipetting (~30%).
Gentle Cell Sorting
Our single cell sorters can preserve the viability and integrity of cells for better clonal outgrowth. The low-pressure sorting by our instruments is gentle on your precious cells.

Empower CRISPR Cell Engineering with Innovative Single Cell Sorting
Discover how scientists are using Bio-Techne's Single Cell Dispensers to empower single cell cloning to generate CRISPR-edited cell lines. Discover the key role that single cell sorting and isolation can play in your cell engineering workflow for a wide range of application from cell biology, to drug discovery and future cell therapy.
Webinar: Producing High Quality CRISPR-Cas9 Edited hiPSCs
Learn from Dr Maks Prondzynski about optimizing the growth and differentiation of human induced pluripotent stem cells (hiPSCs) into cardiomyocytes to support enhancing cardiac disease modelling.