DOI: 10.5061/dryad.0k6djhbd5
title: Data from: A global screen for magnetically induced neuronal activity in the pigeon brain

description: How animals detect the Earth's magnetic field remains a mystery in
 sensory biology. Despite extensive behavioral evidence, the neural
 circuitry and molecular mechanisms responsible for magnetic sensing remain
 elusive. Adopting an unbiased approach, we employ whole-brain activity
 mapping, tissue clearing, and light-sheet microscopy to identify neuronal
 populations activated by magnetic stimuli in the pigeon (Columba livia).
 We demonstrate robust, light-independent neuronal activation in the medial
 vestibular nuclei and the caudal mesopallium. Single-cell RNA sequencing
 of the semicircular cristae revealed specialized type II hair cells that
 express the molecular machinery necessary for the detection of magnetic
 stimuli by electromagnetic induction. Our data supports a model whereby
 electro-magnetic input from the semicircular canals activates a
 vestibular-mesopallial circuit within the pigeon brain.
description: # Data from: A global screen for magnetically induced neuronal activity in
 the pigeon brain Dataset DOI:
 [10.5061/dryad.0k6djhbd5](10.5061/dryad.0k6djhbd5) ## Description of the
 data and file structure Data from: A global screen for magnetically
 induced neuronal activity in the pigeon brain ### Files and variables ####
 File: LSM_analysis_2.tar.gz **Description:** &gt;This repository contains
 whole brain C-FOS detection matrices from unsupervised Clearmap
 processing. These matrices can be voxelized to generate heatmaps. Folder
 structure: MAWB14- light experiment MAWB1- dark experiment MAWB12- static
 experiment Each subfolder is divided by light sheet microscopy acquisition
 quadrant (See figure S1B): DY1-dorsal anterior DY2-dorsal posterior
 VY1-ventral posterior VY2-ventral anterior #### File:
 scRNA_seq_data.tar.gz **Description:** &gt;This repository contains Raw
 single cell RNA-seq data, Seurat objects, and R code for analysis and
 figure generation. ##### Raw_sequencing_data Paired-end reads from the 2
 sub-libraries of cDNA from 10k and 5k pigeon ampullary cells #####
 Parse_Matrix **Description:** Parse_matrix: output after read alignment
 and read deduplication using the splitpipe pipeline. Combined, these files
 reconstruct the count matrix, offering a comprehensive view of the data
 ###### all_genes_anno.csv includes gene names and IDs * *gene_id*:
 annotated gene symbol * *gene_name*: annotated gene symbol * *genome*:
 *Columba livia* (rock pigeon) Cliv_1.0 (GCF_000337935.1) ######
 cell_metadata.csv contains barcode information. * *bc_wells*: Cell barcode
 ID determined by the well numbers of the 96 well plates, from the 3 rounds
 of barcoding followed by the sublibrary ID. * *sample*: Sample ID *
 *species*: Genome name used to align the raw reads * *gene_count*: number
 of genes detected per cell * *tscp_count*: number of transcripts detected
 per cell * *mread_count*: median number of raw sequencing reads detected
 per cell * *bc1_well*: Well ID 1 (row number in the 96 well plate) *
 *bc2_well*: Well ID 2 (row number in the 96 well plate) * *bc3_well*: Well
 ID 3 (row number in the 96 well plate) * *bc1_wind*: Barcode 1 well number
 * *bc2_wind*: Barcode 2 well number * *bc3_wind*: Barcode 3 well number
 ###### DGE.mtx file represents the count data in a compact format.
 Rows=cells, Cols=genes ##### RDS_files This repository contains analysed
 single cell RNA seq data using Seurat V‘4.1.3’. E1APM: QC, log normalised
 and clustered data object created from all transcripts aligned to the
 cliv1.0 reference genome using splitpipe v1.0.6 haircells_merged_object:
 Haircell subset from all transcripts E1APM.markers.rds: Top 100 DEGs of
 cell clusters E1APM3: QC, log normalised and clustered data object created
 from only 3' transcripts aligned to the cliv1.0 reference genome
 using splitpipe v1.0.6 haircells_before_clustering_3p: Haircell subset of
 only 3' transcripts (used to compare gene expression of voltage gated
 ion channels in hair cells) ##### R scripts R code for analysis and figure
 generation #### File: pigeonbrain_clearmap_scripts_2.tar.gz
 **Description:** &gt;This repository contains Clearmap python scripts used
 in this manuscript. Scripts are modified from
 ([http://christophkirst.github.io/ClearMap/build/html/index.html](http://christophkirst.github.io/ClearMap/build/html/index.html)) pigeonbrain_clearmap_permutation.py: Python script to run permutation-based correction strategy on our datasets. Adjust parameters in lines 349-363. pigeonbrain_params_01vy1.py: Python script with example parameters. pigeonbrain_process_template_01vy1.py: Python script executing processing based on paramters above. ## Code/software Use Clearmap ([https://github.com/ChristophKirst/ClearMap](https://github.com/ChristophKirst/ClearMap)) to run whole brain analyses