# A transcriptional rheostat couples past activity to future sensory responses Code and data to replicate analyses in Tsukahara, Brann et al. 2021 Cell https://doi.org/10.1016/j.cell.2021.11.022 ## Summary Animals traversing different environments encounter both stable background stimuli and novel cues, which are thought to be detected by primary sensory neurons and then distinguished by downstream brain circuits. Here we show that each of the ~1000 olfactory sensory neuron (OSN) subtypes in the mouse harbors a distinct transcriptome whose content is precisely determined by interactions between its odorant receptor and the environment. This transcriptional variation is systematically organized to support sensory adaptation: expression levels of more than 70 genes relevant to transforming odors into spikes continuously vary across OSN subtypes, dynamically adjust to new environments over hours, and accurately predict acute OSN-specific odor responses. The sensory periphery therefore separates salient signals from predictable background via a transcriptional rheostat whose moment-to-moment state reflects the past and constrains the future; these findings suggest a general model in which structured transcriptional variation within a cell type reflects individual experience. ## Manuscript For more details, please see our Open Access manuscript: https://www.cell.com/cell/fulltext/S0092-8674(21)01337-4 # Code 1. The code here is a copy of that on GitHub: https://github.com/dattalab/Tsukahara_Brann_OSN. Instructions for how to download and install it can be found in the README.md file. 2. Data is available on the NCBI GEO (accession GSE173947) and raw fastq files are available from the SRA (accession SRP318630). 3. Supplementary data (imaging traces and example preprocessed AnnData object for the home-cage dataset) can be found in the data folders of the attached Tsukahara_Brann_OSN-zenodo.zip file.

{"references": ["Tsukahara, Brann, et al., A transcriptional rheostat couples past activity to future sensory responses, Cell (2021), https://doi.org/10.1016/j.cell.2021.11.022"]}