Summary Ionotropic neurotransmitter receptors mediate fast synaptic transmission by functioning as ligand-gated ion channels. Fast inhibitory transmission in the brain is mediated mostly by ionotropic GABAA receptors (GABAARs), but their essential components for synaptic localization remain unknown. Here, we identify putative auxiliary subunits of GABAARs, which we term GARLHs, consisting of LH4 and LH3 proteins. LH4 forms a stable tripartite complex with GABAARs and neuroligin-2 in the brain. Moreover, LH4 is required for the synaptic localization of GABAARs and inhibitory synaptic transmission in the hippocampus. Our findings propose GARLHs as the first identified auxiliary subunits for anion channels. These findings provide new insights into the regulation of inhibitory transmission and the molecular constituents of native anion channels in vivo.

SUMMARY Background Biological networks experience quantitative change in response to environmental and evolutionary variation. Computational modeling allows exploration of network parameter space, corresponding to such variations. The intercellular signaling network underlying Caenorhabditis vulva development specifies three fates in a row of six precursor cells, yielding a quasi-invariant 3°-3°-2°-1°-2°-3° cell fate pattern. Two seemingly conflicting verbal models of vulval precursor cell fate specification have been proposed: sequential induction by the EGF-MAP kinase and Notch pathways, or morphogen-based induction by the former. Results To study the mechanistic and evolutionary system properties of this network, we combine experimental studies with computational modeling, using a model that keeps the network architecture constant but varies parameters. We first show that the Delta autocrine loop can play an essential role in 2° fate specification. With this autocrine loop, the same network topology can be quantitatively tuned to use in the six-cell row morphogen-based or sequential patterning mechanisms, which may act singly, cooperatively or redundantly. Moreover, different quantitative tunings of this same network can explain vulval patterning observed experimentally in C. elegans, C. briggsae, C. remanei and C. brenneri. We experimentally validate model predictions, such as interspecific differences in isolated vulva precursor cell behavior and in spatial regulation of Notch activity. Conclusions Our study illustrates how quantitative variation in the same network comprises developmental patterning modes that were considered qualitatively distinct and also accounts for evolution among closely related species.