Back

A PCR-RFLP method for the detection of CRISPR-induced indels

Angelopoulou, L.; Stylianopoulou, E.; Tegopoulos, K.; Farmakioti, I.; Grigoriou, M. E.; Skavdis, G.

2023-04-09 molecular biology
10.1101/2023.04.09.535589 bioRxiv
Show abstract

CRISPR-based technologies have revolutionised genome editing and are widely used for knocking out genes in cell lines and organisms. From a practical perspective, a critical factor that largely influences the successful outcome of CRISPR gene knockout experiments is the reliable and fast identification of fully mutated cells carrying exclusively null alleles of the target gene. Here we describe a novel strategy based on the well-documented reliability and simplicity of the classical PCR-Restriction Fragment Length Polymorphism (RFLP), which allows the assessment of the editing efficiency in pools of edited cells and the effective identification of cell clones that carry exclusively mutated alleles. This fast and cost-effective method, named PIM-RFLP (PCR Induced Mutagenesis-RFLP), is executed in two steps. In the first step, the editing target is amplified by a set of mutagenic primers that create a restriction enzyme degenerate cleavage site in the amplification product of the wild type allele. As a proof of principle, we chose the XcmI restriction site because it is especially suitable since it has the particularity of containing nine centrally placed non-specific nucleotides. This gives great flexibility in the mutagenic primers design and allows for efficient execution of the mutagenic PCR. In the second step, the evaluation of the editing efficiency in pools of edited cells or the identification of fully mutated single-cell derived clones is achieved following the standard procedure for any PCR-RFLP assay: digestion of the PCR products and analysis of the restriction fragments in an agarose gel. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/535589v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@131eda6org.highwire.dtl.DTLVardef@e93c43org.highwire.dtl.DTLVardef@736fe5org.highwire.dtl.DTLVardef@b750c1_HPS_FORMAT_FIGEXP M_FIG C_FIG

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.