ArticleMolecular biology reports2013
Targeted editing of goat genome with modular-assembly zinc finger nucleases based on activity prediction by computational molecular modeling.
Article in Molecular biology reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 16 citations in OpenAlex.
- Genome editing: An insight into disease resistance, production efficiency, and biomedical applications in livestock.Functional & integrative genomics · 2024Review
- Improvements of nuclease and nickase gene modification techniques for the treatment of genetic diseases.Frontiers in genome editing · 2022Review
- Review
- Sheep and Goat Genome Engineering: From Random Transgenesis to the CRISPR Era.Frontiers in genetics · 2019Review
Corrections and comments
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Authors and funding
15 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Zinc finger nuclease (ZFN) technology can mediate targeted genome modification to produce transgenic animals in a high-efficient and biological-safe way. Modular assembly is a rapid, convenient and open-source method for the synthesis of ZFNs. However, this biotechnology is hampered by multistep construction, low-efficiency editing and off-target cleavage. Here we synthesized and tested six pairs of three- or four-finger ZFNs to target one site in goat beta-lactoglobulin (BLG, a dominant allergen in goat milk) gene. Homology modeling was applied to build the structure model of ZFNs to predict their editing activities targeting at goat BLG gene. Goat fibroblast cells were transfected with plasmids that encoded ZFN pairs, and genomic DNA was isolated 72 h later for genome editing efficiency assay. The results of editing efficiency assay demonstrated that ZFNs with optimal interaction modes can edit goat BLG gene more efficiently, whereas ZFNs with unexpected interaction modes showed lower activities in editing BLG gene. We concluded that modular-assembly ZFNs can provide a rapid, public-available, and easy-to-practice platform for transgenic animal research and molecular modeling would help as a useful tool for ZFNs activity prediction.
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Registered trials
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