Pre-T cell receptor localization and trafficking are independent of its signaling.

Expression of the pre-T cell receptor (preTCR) is an important checkpoint during the development of T cells, an essential cell type of our adaptive immune system. The preTCR complex is only transiently expressed and rapidly internalized in developing T cells and is thought to signal in a ligand-independent manner. However, identifying a mechanistic basis for these unique features of the preTCR compared with the final TCR complex has been confounded by the concomitant signaling that is normally present. Thus, we have reconstituted preTCR expression in non-immune cells to uncouple receptor trafficking dynamics from its associated signaling. We find that all the defining features of the preTCR are intrinsic properties of the receptor itself, driven by exposure of an extracellular hydrophobic region, and are not the consequence of receptor activation. Finally, we show that transitory preTCR cell surface expression can sustain tonic signaling in the absence of ligand binding, suggesting how the preTCR can nonetheless drive αßTCR lineage commitment.

Systematic analysis of YFP traps reveals common mRNA/protein discordance in neural tissues.

While post-transcriptional control is thought to be required at the periphery of neurons and glia, its extent is unclear. Here, we investigate systematically the spatial distribution and expression of mRNA at single molecule sensitivity and their corresponding proteins of 200 YFP trap lines across the intact Drosophila nervous system. 97.5% of the genes studied showed discordance between the distribution of mRNA and the proteins they encode in at least one region of the nervous system. These data suggest that post-transcriptional regulation is very common, helping to explain the complexity of the nervous system. We also discovered that 68.5% of these genes have transcripts present at the periphery of neurons, with 9.5% at the glial periphery. Peripheral transcripts include many potential new regulators of neurons, glia, and their interactions. Our approach is applicable to most genes and tissues and includes powerful novel data annotation and visualization tools for post-transcriptional regulation.