Resource Core 1 - Primate/rodent Molecular Anatomy Core (PMAC)

Resource Core 1 - Primate/rodent Molecular Anatomy Core (PMAC) Leads: Kristin Overton PhD and Karl Deisseroth MD PhD Summary The PMAC will develop, validate, and implement (in the real-world setting of the U19 team projects/collaborations), next-generation technologies for studying circuit structure-function relationships. The

PMAC involves guided use and refinement of state-of-the-art molecular, viral, and anatomical strategies across projects, continuously adapted and modernized to keep up with (and drive) this fast-moving field over the course of the 5-year overall project. The PMAC will address key technologically-intensive questions that will

continuously arise across projects as three main categories of primate-capable molecular and anatomical tool will be developed for the broader U19 team: 1) latest-generation hydrogel-based volume acquisition, registration, quantification, and analysis across species, including molecular analysis of the same cells with known activity

patterns during behavior via IEG-based activity traces using two of our hydrogel-tissue chemistry methods (CLARITY and STARmap; 2) continuously-updated viral vectors for anatomy/activity visualization and causal control, precision-designed to take into account both animal history (including past virus exposure/immune

status) and spectral overlap relevant to combinatorial usage of multiple optical tools together; and 3) versatile viral tools for tagging (with fluorescent and activity-sensing-or-control tools) circuit elements naturally used during specific behaviors, or for targeting cells based on many features of wiring, activity, and genetics. Aligning

the functional (activity) features of cortical neurons with their genetic profiles is crucial. For the PMAC, we note the superb timing in that our recent development of STARmap (Wang et al. Science 2018) will allow addressing this issue in a general sense, assigning deep typology and rich molecular signature information (hundreds of

genes, and even >1000 genes per cell) to the same individual neurons and ensembles observed to be naturally and causally involved in behavior. The PMAC will pay particular attention to integrative methods for crossing scales of observation, consulting with the DSC regarding effective means for storing and sending the massive

datasets. Analysis of the datasets will be with methods developed by the computational RP3 and the DSC. Results from U19 teams in the course of implementation, relating to optical figures of merit, including signal-to- noise, aberrations, and speed, will be fed back to the PMAC in a tight closed-loop workflow guided by real-world

application, a key opportunity for fundamental science itself.