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Diploid transgenic organisms are either hemi- or homozygous. Genetic assays are, therefore, required to identify the genotype. Our AGameOfClones vector concept uses two clearly distinguishable transformation markers embedded in interweaved, but incompatible Lox site pairs. Cre-mediated recombination leads to hemizygous individuals that carry only one marker. In the following generation, heterozygous descendants are identified by the presence of both markers and produce homozygous progeny that are selected by the lack of one marker. We prove our concept in Tribolium castaneum by systematically creating multiple functional homozygous transgenic lines suitable for long-term fluorescence live imaging. Our approach saves resources and simplifies transgenic organism handling. Since the concept relies on the universal Cre-Lox system, it is expected to work in all diploid model organisms, for example, insects, zebrafish, rodents and plants. With appropriate adaptions, it can be used in knock-out assays to preselect homozygous individuals and thus minimize the number of wasted animals.
Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.