Gene Knockout Efficiency
Gene Knockout Efficiency - Related Videos
11:53
A Protocol for Multiple Gene Knockout in Mouse Small Intestinal Organoids Using a CRISPR-concatemer
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Cited by 17 •
2017
This protocol describes the steps for cloning multiple single guide RNAs into one guide RNA concatemer vector, which is of particular use in creating multi-gene knockouts using CRISPR/Cas9 technology. The generation of double knockouts in intestinal organoids is shown as a possible application of this method.
04:13
CRISPR Concatemer-Mediated Multiple Gene Knockout: A Technique to Simultaneously Knockout Multiple Genes by Non-Homologous End-Joining Pathway in Mouse Intestinal Cells
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2025
This video describes a gene knockout technique using a CRISPR-concatemer to simultaneously knock out multiple genes in cultured mouse intestinal organoid cells. This method is used to knock out a diseased gene and to elucidate the function of a gene and its paralogues.
02:29
In-vitro Mutagenesis (Gene Knockouts)
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2026
To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes. The Process Genes can be randomly knocked out, or specific genes can be targeted. To knock out a particular gene, an engineered piece of DNA called a targeting vector is used to replace the...
12:55
Using the Gene Pulser MXcell Electroporation System to Transfect Primary Cells with High Efficiency
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Cited by 11 •
2010
This procedure shows how to use the Gene Pulser MXcell electroporation system to rapidly and easily identify the best electroporation conditions for mouse embryonic fibroblasts (MEFs) or other primary cells. Considerations for troubleshooting are also discussed in the associated video.
11:27
Efficient Production and Identification of CRISPR/Cas9-generated Gene Knockouts in the Model System Danio rerio
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Cited by 34 •
2018
Targeted genome editing in the model system Danio rerio (zebrafish) has been greatly facilitated by the emergence of CRISPR-based approaches. Herein, we describe a streamlined, robust protocol for generation and identification of CRISPR-derived nonsense alleles that incorporates the heteroduplex mobility assay and identification of mutations using next-generation sequencing.
FAQs
Performance reflects several interacting variables rather than guide choice alone. Guide design determines how the target is addressed, while delivery affects whether editing components reach cells. Cell type can alter the response, and the genomic locus influences the result. Considering these variables together helps investigators optimize conditions instead of attributing low efficiency to a single cause.
After Cas9 creates a site-specific DNA break, error-prone end joining can repair it with insertions or deletions. These changes may disrupt the selected gene, but their size and position determine whether gene function is actually lost. Consequently, a high frequency of edited DNA does not automatically establish complete knockout across all targeted cells.
An editing event becomes functionally meaningful only when the resulting DNA change interferes with the chosen gene. Cas9 supplies the targeted break, whereas repair generates the sequence alterations that may disrupt it. This division of roles explains why measuring the break or an edit alone is insufficient; researchers must determine whether gene activity has been eliminated or only partially affected.
Evaluation can combine genotyping, sequencing, and protein-level assays. Genotyping indicates whether the target region has changed, sequencing characterizes the resulting insertions or deletions, and protein analysis tests whether gene product remains. Using these readouts together provides stronger evidence than relying on one measurement and helps identify whether editing conditions require further optimization.
Researchers compare the frequency and nature of target-site changes with evidence from protein-level assays. Sequencing can reveal heterogeneous insertions or deletions among cells, while protein analysis indicates whether gene product persists. This distinction matters because a mixed or partial result can complicate phenotype interpretation and may require optimization before functional conclusions are drawn.
It supports functional genomics by linking gene disruption to observed phenotypes, and it helps establish the reliability of disease models. The same measurements are relevant in biotechnology, where investigators need to interpret outcomes from engineered cells or organisms. Efficiency data therefore provide context for judging whether a phenotype reflects intended gene inactivation.