Data from: A global screen for magnetically induced neuronal activity in the pigeon brain
Data files
Jan 20, 2026 version files 80.31 GB
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LSM_analysis_2.tar.gz
4.75 GB
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pigeonbrain_clearmap_scripts_2.tar.gz
51.20 KB
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README.md
3.83 KB
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scRNA_seq_data.tar.gz
75.56 GB
Abstract
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.
Dataset DOI: 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: >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: >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
- gene_id: annotated gene symbol
- gene_name: annotated gene symbol
- genome: Columba livia (rock pigeon) Cliv_1.0 (GCF_000337935.1)
- 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
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: >This repository contains Clearmap python scripts used in this manuscript. Scripts are modified from (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) to run whole brain analyses