
doi: 10.1155/2014/324839
Long QT 7 syndrome (LQT7, also known as Andersen-Tawil syndrome) is a rare autosomal-dominant disorder that causes cardiac arrhythmias, periodic paralysis, and dysmorphic features. Mutations in the humanKCNJ2gene, which encodes for the subunit of the potassium inwardly-rectifying channel (IK1), have been associated with the disorder. The majority of mutations are considered to be dominant-negative as mutant proteins interact to limit the function of wild type KCNJ2 proteins. Several LQT7 syndrome mouse models have been created that vary in the physiological similarity to the human disease. To complement the LQT7 mouse models, we investigated the usefulness of the zebrafish as an alternative model via a transient approach. Initial bioinformatic analysis identified the zebrafish orthologue of the humanKCNJ2gene, together with a spatial expression profile that was similar to that of human. The expression of akcnj2-12transcript carrying an in-frame deletion of critical amino acids identified in human studies resulted in embryos that exhibited defects in muscle development, thereby affecting movement, a decrease in jaw size, pupil-pupil distance, and signs of scoliosis. These defects correspond to some phenotypes expressed by human LQT7 patients.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
