Animals exhibit significant variation in their behavior among individuals. Several factors contribute to this variability, including genetic variation that impact the development and function of the nervous system. Therefore, to understand the neuronal circuits that influence behavior in a natural context, it is necessary to manipulate neuronal activity within a genetically diverse context. Here, we present an approach that combines genetic diversity with transgenic tools to manipulate neuronal activity and measure its behavioral effects.

We used Drosophila melanogaster, a model organism with an extensive genetic tool set to manipulate neuronal activity and a variety of wild-derived lines with genetic variation amongst themselves. To obtain animals with different genetic backgrounds in a versatile and scalable process, we used heterozygote animals as test subjects. Half of the genome of these animals derive from a standardized genetic background, where the necessary genetics tools to manipulate neuronal activity are used. The other half derives from different genetic backgrounds of the Drosophila genetic reference panel (DGRP). This allowed us to survey the effects of genetic variants that act as dominant alleles.

We focused on the flies' response to a looming stimulus, which simulates an approaching object and typically triggers flight or freezing responses. Control flies, with no neuronal manipulation, from 14 different genetic backgrounds (~200 flies per genetic background), exhibited genetically dependent variation in their responses, validating the use of heterozygote animals. It has been previously described that the descending neuron DNp09 impacts freezing behavior. We inhibited DNp09 in the same 14 genetic backgrounds with Tetanus toxin (TNT, ~200 flies per genetic background). The targeting of TNT expression in this single pair of neurons was maintained in all tested genetic backgrounds. Behavioral assays show that inhibition of DNp09 reduces the probability of entering the freezing state, independently of genetic background. The probability of breaking from freezing is reduced in all genetic backgrounds, but in this case, dependent on the genetic background. These results suggest that DNp09 is an essential node in the neuronal network to maintain the freezing state in a natural context, but that freezing entry may be compensated by other neurons in the network.