The High Throughput Genome Engineering (HTGE) facility provides affordable access to high throughput functional genomic screens using the CRISPR/Cas9 system in cell lines. Pooled CRISPR/Cas9 screening enables parallel interrogation of thousands to tens of thousands of genes for involvement in biological processes of interest. HTGE provides access to verified lentiviral CRISPR guide libraries for whole genome and more targeted loss- and gain of function studies (CRISPR knock-out, CRISPR inhibition, CRISPR activation). We also offer generation of stable Cas9-expressing lines in users’ cells of interest. CRISPR gene perturbation followed by single cell RNASeq is under development together with Eukaryotic Single Cell Genomics (ESCG), and we are developing base-editing approaches to mutagenize sequences to, for example, characterize protein-protein or protein-drug interactions. HTGE foremost aim is to offer state-of-the-art services, and we are happy to implement new screening technologies in collaboration with interested clients.  HTGE supports the Swedish research community with CRISPR screening projects from planning to data analysis.

Our local branch, Karolinska Genome Engineering (KGE), performs precision edits in cell lines, such as knock-out, knock-in, deletions, point mutations, etc. KGE collaborate with the Karolinska Center for Transgene Technologies (KCTT) to offer CRISPR technology in mouse, and is implementing a pipeline with the iPSC core facility for precision editing of iPSCs.

From left to right: Soniya, Jenna, Bernhard, Georgia, Allegra. Photo: Christos Coucoravas

Your project is out of the box? All the better, we would love to hear from you!

Latest innovation available at HTGE:

CRISPR/Cas9 Screening Using Unique Molecular Identifiers. Bernhard Schmierer, Sandeep K. Botla, Jilin Zhang, Mikko Turunen, Teemu Kivioja, Jussi Taipale. Molecular Systems Biology 2017. PDF. Full text.

The precision and accuracy of CRISPR/Cas9 screens is dramatically improved by the incorporation of inert, random sequence labels (RSLs) into CRISPR guides.

• Compared to the conventional method, inclusion of RSLs generates considerably more information at an identical experimental scale and enables data analysis by simple statistics.
• RSL‐based analysis requires fewer cells per guide to reach a set statistical power. This is important if cell numbers are limiting, such as in very large, genome‐wide screens and/or screens in primary cells.
• RSLs can be used as Unique Molecular Identifiers (UMIs), allowing tracking of single cells and their progeny throughout a pooled screen.